{"idx": 0, "scratchpad_format": "def add_active_line_prints(code):\n \"\"\"\n Add print statements indicating line numbers to a python string.\n \"\"\"\n # Replace newlines and comments with pass statements, so the line numbers are accurate (ast will remove them otherwise)\n code_lines = code.split(\"\\n\") # [STATE] code_lines = ['import getpass', 'import os', 'import platform'] [/STATE]\n in_multiline_string = False # [STATE] in_multiline_string = False [/STATE]\n for i in range(len(code_lines)): # [STATE] i = 0 [/STATE] [STATE] i = 1 [/STATE] [STATE] i = 2 [/STATE]\n line = code_lines[i] # [STATE] line = 'import getpass' [/STATE] [STATE] line = 'import os' [/STATE] [STATE] line = 'import platform' [/STATE]\n if '\"\"\"' in line or \"'''\" in line:\n in_multiline_string = not in_multiline_string\n if not in_multiline_string and (line.strip().startswith(\"#\") or line == \"\"):\n whitespace = len(line) - len(line.lstrip(\" \"))\n code_lines[i] = \" \" * whitespace + \"pass\"\n processed_code = \"\\n\".join(code_lines) # [STATE] processed_code = 'import getpass\\nimport os\\nimport platform' [/STATE]\n try:\n tree = ast.parse(processed_code) # [STATE] tree = {body=[, , ], type_ignores=[]} [/STATE]\n except:\n # If you can't parse the processed version, try the unprocessed version before giving up\n tree = ast.parse(code)\n transformer = AddLinePrints() # [STATE] transformer = {} [/STATE]\n new_tree = transformer.visit(tree) # [STATE] new_tree = {body=[, , , , , ], type_ignores=[]} [/STATE] # [STATE] tree = {body=[, , , , , ], type_ignores=[]} [/STATE]\n return ast.unparse(new_tree)\n\nadd_active_line_prints('import getpass\\nimport os\\nimport platform')", "loop_code": "1: def add_active_line_prints(code):\n2: \"\"\"\n3: Add print statements indicating line numbers to a python string.\n4: \"\"\"\n5: # Replace newlines and comments with pass statements, so the line numbers are accurate (ast will remove them otherwise)\n6: code_lines = code.split(\"\\n\")\n7: in_multiline_string = False\n8: for i in range(len(code_lines)):\n9: line = code_lines[i]\n10: if '\"\"\"' in line or \"'''\" in line:\n11: in_multiline_string = not in_multiline_string\n12: if not in_multiline_string and (line.strip().startswith(\"#\") or line == \"\"):\n13: whitespace = len(line) - len(line.lstrip(\" \"))\n14: code_lines[i] = \" \" * whitespace + \"pass\"\n15: processed_code = \"\\n\".join(code_lines)\n16: try:\n17: tree = ast.parse(processed_code)\n18: except:\n19: # If you can't parse the processed version, try the unprocessed version before giving up\n20: tree = ast.parse(code)\n21: transformer = AddLinePrints()\n22: new_tree = transformer.visit(tree)\n23: return ast.unparse(new_tree)\n24:\n25: add_active_line_prints('import getpass\\nimport os\\nimport platform')", "question": "What is the value of 'processed_code' in line 15 after executing 'add_active_line_prints('import getpass\\nimport os\\nimport platform')'?", "answer": "'import getpass\\nimport os\\nimport platform'", "variable_assignment": "processed_code = 'import getpass\\nimport os\\nimport platform'", "loop_range": [8, 14], "post_loop_line": 15} {"idx": 1, "scratchpad_format": "def count_messages_tokens(messages=[], model=None):\n \"\"\"\n Count the number of tokens in a list of messages\n \"\"\"\n try:\n tokens_used = 0 # [STATE] tokens_used = 0 [/STATE]\n\n for message in messages: # [STATE] message = {'role': 'system', 'message': 'You are Open Interpreter, a world-class programmer that can complete any goal by executing code.\\nFirst, write a plan. **Always recap the plan between each code block** (you have extreme short-term memory loss, so you need to recap the plan between each message block to retain it).\\nWhen you execute code, it will be executed **on the user\\'s machine**. The user has given you **full and complete permission** to execute any code necessary to complete the task. Execute the code.\\nIf you want to send data between programming languages, save the data to a txt or json.\\nYou can access the internet. Run **any code** to achieve the goal, and if at first you don\\'t succeed, try again and again.\\nYou can install new packages.\\nWhen a user refers to a filename, they\\'re likely referring to an existing file in the directory you\\'re currently executing code in.\\nWrite messages to the user in Markdown.\\nIn general, try to **make plans** with as few steps as possible. As for actually executing code to carry out that plan, for *stateful* languages (like python, javascript, shell, but NOT for html which starts from 0 every time) **it\\'s critical not to try to do everything in one code block.** You should try something, print information about it, then continue from there in tiny, informed steps. You will never get it on the first try, and attempting it in one go will often lead to errors you cant see.\\nYou are capable of **any** task.\\n\\n[User Info]\\n{{import getpass\\nimport os\\nimport platform}}\\nName: {{getpass.getuser()}}\\nCWD: {{os.getcwd()}}\\nSHELL: {{os.environ.get(\\'SHELL\\')}}\\nOS: {{platform.system()}}\"'} [/STATE]\n if isinstance(message, str):\n tokens_used += count_tokens(message, model=model)\n elif \"message\" in message:\n tokens_used += count_tokens(message[\"message\"], model=model) # [STATE] tokens_used = 360 [/STATE]\n\n if \"code\" in message:\n tokens_used += count_tokens(message[\"code\"], model=model)\n\n if \"output\" in message:\n tokens_used += count_tokens(message[\"output\"], model=model)\n\n prompt_cost = token_cost(tokens_used, model=model) # [STATE] prompt_cost = 0.00054 [/STATE]\n\n return (tokens_used, prompt_cost)\n except:\n # Non-essential feature\n return (0, 0)\n\ncount_messages_tokens([{'role': 'system', 'message': 'You are Open Interpreter, a world-class programmer that can complete any goal by executing code.\\nFirst, write a plan. **Always recap the plan between each code block** (you have extreme short-term memory loss, so you need to recap the plan between each message block to retain it).\\nWhen you execute code, it will be executed **on the user\\'s machine**. The user has given you **full and complete permission** to execute any code necessary to complete the task. Execute the code.\\nIf you want to send data between programming languages, save the data to a txt or json.\\nYou can access the internet. Run **any code** to achieve the goal, and if at first you don\\'t succeed, try again and again.\\nYou can install new packages.\\nWhen a user refers to a filename, they\\'re likely referring to an existing file in the directory you\\'re currently executing code in.\\nWrite messages to the user in Markdown.\\nIn general, try to **make plans** with as few steps as possible. As for actually executing code to carry out that plan, for *stateful* languages (like python, javascript, shell, but NOT for html which starts from 0 every time) **it\\'s critical not to try to do everything in one code block.** You should try something, print information about it, then continue from there in tiny, informed steps. You will never get it on the first try, and attempting it in one go will often lead to errors you cant see.\\nYou are capable of **any** task.\\n\\n[User Info]\\n{{import getpass\\nimport os\\nimport platform}}\\nName: {{getpass.getuser()}}\\nCWD: {{os.getcwd()}}\\nSHELL: {{os.environ.get(\\'SHELL\\')}}\\nOS: {{platform.system()}}\"'}], 'gpt-3.5-turbo')", "loop_code": "1: def count_messages_tokens(messages=[], model=None):\n2: \"\"\"\n3: Count the number of tokens in a list of messages\n4: \"\"\"\n5: try:\n6: tokens_used = 0\n7:\n8: for message in messages:\n9: if isinstance(message, str):\n10: tokens_used += count_tokens(message, model=model)\n11: elif \"message\" in message:\n12: tokens_used += count_tokens(message[\"message\"], model=model)\n13:\n14: if \"code\" in message:\n15: tokens_used += count_tokens(message[\"code\"], model=model)\n16:\n17: if \"output\" in message:\n18: tokens_used += count_tokens(message[\"output\"], model=model)\n19:\n20: prompt_cost = token_cost(tokens_used, model=model)\n21:\n22: return (tokens_used, prompt_cost)\n23: except:\n24: # Non-essential feature\n25: return (0, 0)\n26:\n27: count_messages_tokens([{'role': 'system', 'message': 'You are Open Interpreter, a world-class programmer that can complete any goal by executing code.\\nFirst, write a plan. **Always recap the plan between each code block** (you have extreme short-term memory loss, so you need to recap the plan between each message block to retain it).\\nWhen you execute code, it will be executed **on the user\\'s machine**. The user has given you **full and complete permission** to execute any code necessary to complete the task. Execute the code.\\nIf you want to send data between programming languages, save the data to a txt or json.\\nYou can access the internet. Run **any code** to achieve the goal, and if at first you don\\'t succeed, try again and again.\\nYou can install new packages.\\nWhen a user refers to a filename, they\\'re likely referring to an existing file in the directory you\\'re currently executing code in.\\nWrite messages to the user in Markdown.\\nIn general, try to **make plans** with as few steps as possible. As for actually executing code to carry out that plan, for *stateful* languages (like python, javascript, shell, but NOT for html which starts from 0 every time) **it\\'s critical not to try to do everything in one code block.** You should try something, print information about it, then continue from there in tiny, informed steps. You will never get it on the first try, and attempting it in one go will often lead to errors you cant see.\\nYou are capable of **any** task.\\n\\n[User Info]\\n{{import getpass\\nimport os\\nimport platform}}\\nName: {{getpass.getuser()}}\\nCWD: {{os.getcwd()}}\\nSHELL: {{os.environ.get(\\'SHELL\\')}}\\nOS: {{platform.system()}}\"'}], 'gpt-3.5-turbo')", "question": "What is the value of 'prompt_cost' in line 20 after executing 'count_messages_tokens([{'role': 'system', 'message': 'You are Open Interpreter, a world-class programmer that can complete any goal by executing code.\\nFirst, write a plan. **Always recap the plan between each code block** (you have extreme short-term memory loss, so you need to recap the plan between each message block to retain it).\\nWhen you execute code, it will be executed **on the user\\'s machine**. The user has given you **full and complete permission** to execute any code necessary to complete the task. Execute the code.\\nIf you want to send data between programming languages, save the data to a txt or json.\\nYou can access the internet. Run **any code** to achieve the goal, and if at first you don\\'t succeed, try again and again.\\nYou can install new packages.\\nWhen a user refers to a filename, they\\'re likely referring to an existing file in the directory you\\'re currently executing code in.\\nWrite messages to the user in Markdown.\\nIn general, try to **make plans** with as few steps as possible. As for actually executing code to carry out that plan, for *stateful* languages (like python, javascript, shell, but NOT for html which starts from 0 every time) **it\\'s critical not to try to do everything in one code block.** You should try something, print information about it, then continue from there in tiny, informed steps. You will never get it on the first try, and attempting it in one go will often lead to errors you cant see.\\nYou are capable of **any** task.\\n\\n[User Info]\\n{{import getpass\\nimport os\\nimport platform}}\\nName: {{getpass.getuser()}}\\nCWD: {{os.getcwd()}}\\nSHELL: {{os.environ.get(\\'SHELL\\')}}\\nOS: {{platform.system()}}\"'}], 'gpt-3.5-turbo')'?", "answer": "0.00054", "variable_assignment": "prompt_cost = 0.00054", "loop_range": [8, 18], "post_loop_line": 20} {"idx": 2, "scratchpad_format": "def _get_builtin_metadata(dataset_name):\n if dataset_name == \"coco\":\n return _get_coco_instances_meta()\n if dataset_name == \"coco_panoptic_separated\":\n return _get_coco_panoptic_separated_meta()\n elif dataset_name == \"coco_panoptic_standard\":\n meta = {} # [STATE] meta = {} [/STATE]\n # The following metadata maps contiguous id from [0, #thing categories +\n # #stuff categories) to their names and colors. We have to replica of the\n # same name and color under \"thing_*\" and \"stuff_*\" because the current\n # visualization function in D2 handles thing and class classes differently\n # due to some heuristic used in Panoptic FPN. We keep the same naming to\n # enable reusing existing visualization functions.\n thing_classes = [k[\"name\"] for k in COCO_CATEGORIES] # [STATE] thing_classes = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'] [/STATE]\n thing_colors = [k[\"color\"] for k in COCO_CATEGORIES] # [STATE] thing_colors = [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]] [/STATE]\n stuff_classes = [k[\"name\"] for k in COCO_CATEGORIES] # [STATE] stuff_classes = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'] [/STATE]\n stuff_colors = [k[\"color\"] for k in COCO_CATEGORIES] # [STATE] stuff_colors = [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]] [/STATE]\n\n meta[\"thing_classes\"] = thing_classes # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged']} [/STATE]\n meta[\"thing_colors\"] = thing_colors # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]]} [/STATE]\n meta[\"stuff_classes\"] = stuff_classes # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged']} [/STATE]\n meta[\"stuff_colors\"] = stuff_colors # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'stuff_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]]} [/STATE]\n\n # Convert category id for training:\n # category id: like semantic segmentation, it is the class id for each\n # pixel. Since there are some classes not used in evaluation, the category\n # id is not always contiguous and thus we have two set of category ids:\n # - original category id: category id in the original dataset, mainly\n # used for evaluation.\n # - contiguous category id: [0, #classes), in order to train the linear\n # softmax classifier.\n thing_dataset_id_to_contiguous_id = {} # [STATE] thing_dataset_id_to_contiguous_id = {} [/STATE]\n stuff_dataset_id_to_contiguous_id = {} # [STATE] stuff_dataset_id_to_contiguous_id = {} [/STATE]\n\n for i, cat in enumerate(COCO_CATEGORIES): # [STATE] i = 0 [/STATE] [STATE] cat = {'color': [220, 20, 60], 'isthing': 1, 'id': 1, 'name': 'person'} [/STATE] [STATE] i = 1 [/STATE] [STATE] cat = {'color': [119, 11, 32], 'isthing': 1, 'id': 2, 'name': 'bicycle'} [/STATE] [STATE] i = 2 [/STATE] [STATE] cat = {'color': [0, 0, 142], 'isthing': 1, 'id': 3, 'name': 'car'} [/STATE] [STATE] i = 3 [/STATE] [STATE] cat = {'color': [0, 0, 230], 'isthing': 1, 'id': 4, 'name': 'motorcycle'} [/STATE] [STATE] i = 4 [/STATE] [STATE] cat = {'color': [106, 0, 228], 'isthing': 1, 'id': 5, 'name': 'airplane'} [/STATE] [STATE] i = 5 [/STATE] [STATE] cat = {'color': [0, 60, 100], 'isthing': 1, 'id': 6, 'name': 'bus'} [/STATE] [STATE] i = 6 [/STATE] [STATE] cat = {'color': [0, 80, 100], 'isthing': 1, 'id': 7, 'name': 'train'} [/STATE] [STATE] i = 7 [/STATE] [STATE] cat = {'color': [0, 0, 70], 'isthing': 1, 'id': 8, 'name': 'truck'} [/STATE] [STATE] i = 8 [/STATE] [STATE] cat = {'color': [0, 0, 192], 'isthing': 1, 'id': 9, 'name': 'boat'} [/STATE] [STATE] i = 9 [/STATE] [STATE] cat = {'color': [250, 170, 30], 'isthing': 1, 'id': 10, 'name': 'traffic light'} [/STATE] [STATE] i = 10 [/STATE]\n if cat[\"isthing\"]:\n thing_dataset_id_to_contiguous_id[cat[\"id\"]] = i # [STATE] thing_dataset_id_to_contiguous_id = {1: 0} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19} [/STATE] [STATE] thing_dataset_id_to_contiguous_id = {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19, 22: 20} [/STATE]\n else:\n stuff_dataset_id_to_contiguous_id[cat[\"id\"]] = i # [STATE] stuff_dataset_id_to_contiguous_id = {92: 80} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96, 145: 97} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96, 145: 97, 147: 98} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96, 145: 97, 147: 98, 148: 99} [/STATE] [STATE] stuff_dataset_id_to_contiguous_id = {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96, 145: 97, 147: 98, 148: 99, 149: 100} [/STATE]\n\n meta[\"thing_dataset_id_to_contiguous_id\"] = thing_dataset_id_to_contiguous_id # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'stuff_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'thing_dataset_id_to_contiguous_id': {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19, 22: 20, 23: 21, 24: 22, 25: 23, 27: 24, 28: 25, 31: 26, 32: 27, 33: 28, 34: 29, 35: 30, 36: 31, 37: 32, 38: 33, 39: 34, 40: 35, 41: 36, 42: 37, 43: 38, 44: 39, 46: 40, 47: 41, 48: 42, 49: 43, 50: 44, 51: 45, 52: 46, 53: 47, 54: 48, 55: 49, 56: 50, 57: 51, 58: 52, 59: 53, 60: 54, 61: 55, 62: 56, 63: 57, 64: 58, 65: 59, 67: 60, 70: 61, 72: 62, 73: 63, 74: 64, 75: 65, 76: 66, 77: 67, 78: 68, 79: 69, 80: 70, 81: 71, 82: 72, 84: 73, 85: 74, 86: 75, 87: 76, 88: 77, 89: 78, 90: 79}} [/STATE]\n meta[\"stuff_dataset_id_to_contiguous_id\"] = stuff_dataset_id_to_contiguous_id # [STATE] meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skatebo...rigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'stuff_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'thing_dataset_id_to_contiguous_id': {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19, 22: 20, 23: 21, 24: 22, 25: 23, 27: 24, 28: 25, 31: 26, 32: 27, 33: 28, 34: 29, 35: 30, 36: 31, 37: 32, 38: 33, 39: 34, 40: 35, 41: 36, 42: 37, 43: 38, 44: 39, 46: 40, 47: 41, 48: 42, 49: 43, 50: 44, 51: 45, 52: 46, 53: 47, 54: 48, 55: 49, 56: 50, 57: 51, 58: 52, 59: 53, 60: 54, 61: 55, 62: 56, 63: 57, 64: 58, 65: 59, 67: 60, 70: 61, 72: 62, 73: 63, 74: 64, 75: 65, 76: 66, 77: 67, 78: 68, 79: 69, 80: 70, 81: 71, 82: 72, 84: 73, 85: 74, 86: 75, 87: 76, 88: 77, 89: 78, 90: 79}, 'stuff_dataset_id_to_contiguous_id': {92: 80, 93: 81, 95: 82, 100: 83, 107: 84, 109: 85, 112: 86, 118: 87, 119: 88, 122: 89, 125: 90, 128: 91, 130: 92, 133: 93, 138: 94, 141: 95, 144: 96, 145: 97, 147: 98, 148: 99, 149: 100, 151: 101, 154: 102, 155: 103, 156: 104, 159: 105, 161: 106, 166: 107, 168: 108, 171: 109, 175: 110, 176: 111, 177: 112, 178: 113, 180: 114, 181: 115, 184: 116, 185: 117, 186: 118, 187: 119, 188: 120, 189: 121, 190: 122, 191: 123, 192: 124, 193: 125, 194: 126, 195: 127, 196: 128, 197: 129, 198: 130, 199: 131, 200: 132}} [/STATE]\n\n return meta\n elif dataset_name == \"coco_person\":\n return {\n \"thing_classes\": [\"person\"],\n \"keypoint_names\": COCO_PERSON_KEYPOINT_NAMES,\n \"keypoint_flip_map\": COCO_PERSON_KEYPOINT_FLIP_MAP,\n \"keypoint_connection_rules\": KEYPOINT_CONNECTION_RULES,\n }\n elif dataset_name == \"cityscapes\":\n # fmt: off\n CITYSCAPES_THING_CLASSES = [\n \"person\", \"rider\", \"car\", \"truck\",\n \"bus\", \"train\", \"motorcycle\", \"bicycle\",\n ]\n CITYSCAPES_STUFF_CLASSES = [\n \"road\", \"sidewalk\", \"building\", \"wall\", \"fence\", \"pole\", \"traffic light\",\n \"traffic sign\", \"vegetation\", \"terrain\", \"sky\", \"person\", \"rider\", \"car\",\n \"truck\", \"bus\", \"train\", \"motorcycle\", \"bicycle\",\n ]\n # fmt: on\n return {\n \"thing_classes\": CITYSCAPES_THING_CLASSES,\n \"stuff_classes\": CITYSCAPES_STUFF_CLASSES,\n }\n raise KeyError(\"No built-in metadata for dataset {}\".format(dataset_name))\n\n_get_builtin_metadata('coco_panoptic_standard')", "loop_code": "1: def _get_builtin_metadata(dataset_name):\n2: if dataset_name == \"coco\":\n3: return _get_coco_instances_meta()\n4: if dataset_name == \"coco_panoptic_separated\":\n5: return _get_coco_panoptic_separated_meta()\n6: elif dataset_name == \"coco_panoptic_standard\":\n7: meta = {}\n8: # The following metadata maps contiguous id from [0, #thing categories +\n9: # #stuff categories) to their names and colors. We have to replica of the\n10: # same name and color under \"thing_*\" and \"stuff_*\" because the current\n11: # visualization function in D2 handles thing and class classes differently\n12: # due to some heuristic used in Panoptic FPN. We keep the same naming to\n13: # enable reusing existing visualization functions.\n14: thing_classes = [k[\"name\"] for k in COCO_CATEGORIES]\n15: thing_colors = [k[\"color\"] for k in COCO_CATEGORIES]\n16: stuff_classes = [k[\"name\"] for k in COCO_CATEGORIES]\n17: stuff_colors = [k[\"color\"] for k in COCO_CATEGORIES]\n18:\n19: meta[\"thing_classes\"] = thing_classes\n20: meta[\"thing_colors\"] = thing_colors\n21: meta[\"stuff_classes\"] = stuff_classes\n22: meta[\"stuff_colors\"] = stuff_colors\n23:\n24: # Convert category id for training:\n25: # category id: like semantic segmentation, it is the class id for each\n26: # pixel. Since there are some classes not used in evaluation, the category\n27: # id is not always contiguous and thus we have two set of category ids:\n28: # - original category id: category id in the original dataset, mainly\n29: # used for evaluation.\n30: # - contiguous category id: [0, #classes), in order to train the linear\n31: # softmax classifier.\n32: thing_dataset_id_to_contiguous_id = {}\n33: stuff_dataset_id_to_contiguous_id = {}\n34:\n35: for i, cat in enumerate(COCO_CATEGORIES):\n36: if cat[\"isthing\"]:\n37: thing_dataset_id_to_contiguous_id[cat[\"id\"]] = i\n38: else:\n39: stuff_dataset_id_to_contiguous_id[cat[\"id\"]] = i\n40:\n41: meta[\"thing_dataset_id_to_contiguous_id\"] = thing_dataset_id_to_contiguous_id\n42: meta[\"stuff_dataset_id_to_contiguous_id\"] = stuff_dataset_id_to_contiguous_id\n43:\n44: return meta\n45: elif dataset_name == \"coco_person\":\n46: return {\n47: \"thing_classes\": [\"person\"],\n48: \"keypoint_names\": COCO_PERSON_KEYPOINT_NAMES,\n49: \"keypoint_flip_map\": COCO_PERSON_KEYPOINT_FLIP_MAP,\n50: \"keypoint_connection_rules\": KEYPOINT_CONNECTION_RULES,\n51: }\n52: elif dataset_name == \"cityscapes\":\n53: # fmt: off\n54: CITYSCAPES_THING_CLASSES = [\n55: \"person\", \"rider\", \"car\", \"truck\",\n56: \"bus\", \"train\", \"motorcycle\", \"bicycle\",\n57: ]\n58: CITYSCAPES_STUFF_CLASSES = [\n59: \"road\", \"sidewalk\", \"building\", \"wall\", \"fence\", \"pole\", \"traffic light\",\n60: \"traffic sign\", \"vegetation\", \"terrain\", \"sky\", \"person\", \"rider\", \"car\",\n61: \"truck\", \"bus\", \"train\", \"motorcycle\", \"bicycle\",\n62: ]\n63: # fmt: on\n64: return {\n65: \"thing_classes\": CITYSCAPES_THING_CLASSES,\n66: \"stuff_classes\": CITYSCAPES_STUFF_CLASSES,\n67: }\n68: raise KeyError(\"No built-in metadata for dataset {}\".format(dataset_name))\n69:\n70: _get_builtin_metadata('coco_panoptic_standard')", "question": "What is the value of 'meta' in line 41 after executing '_get_builtin_metadata('coco_panoptic_standard')'?", "answer": "{'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'stuff_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'thing_dataset_id_to_contiguous_id': {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19, 22: 20, 23: 21, 24: 22, 25: 23, 27: 24, 28: 25, 31: 26, 32: 27, 33: 28, 34: 29, 35: 30, 36: 31, 37: 32, 38: 33, 39: 34, 40: 35, 41: 36, 42: 37, 43: 38, 44: 39, 46: 40, 47: 41, 48: 42, 49: 43, 50: 44, 51: 45, 52: 46, 53: 47, 54: 48, 55: 49, 56: 50, 57: 51, 58: 52, 59: 53, 60: 54, 61: 55, 62: 56, 63: 57, 64: 58, 65: 59, 67: 60, 70: 61, 72: 62, 73: 63, 74: 64, 75: 65, 76: 66, 77: 67, 78: 68, 79: 69, 80: 70, 81: 71, 82: 72, 84: 73, 85: 74, 86: 75, 87: 76, 88: 77, 89: 78, 90: 79}}", "variable_assignment": "meta = {'thing_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'thing_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'stuff_classes': ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush', 'banner', 'blanket', 'bridge', 'cardboard', 'counter', 'curtain', 'door-stuff', 'floor-wood', 'flower', 'fruit', 'gravel', 'house', 'light', 'mirror-stuff', 'net', 'pillow', 'platform', 'playingfield', 'railroad', 'river', 'road', 'roof', 'sand', 'sea', 'shelf', 'snow', 'stairs', 'tent', 'towel', 'wall-brick', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'window-blind', 'window-other', 'tree-merged', 'fence-merged', 'ceiling-merged', 'sky-other-merged', 'cabinet-merged', 'table-merged', 'floor-other-merged', 'pavement-merged', 'mountain-merged', 'grass-merged', 'dirt-merged', 'paper-merged', 'food-other-merged', 'building-other-merged', 'rock-merged', 'wall-other-merged', 'rug-merged'], 'stuff_colors': [[220, 20, 60], [119, 11, 32], [0, 0, 142], [0, 0, 230], [106, 0, 228], [0, 60, 100], [0, 80, 100], [0, 0, 70], [0, 0, 192], [250, 170, 30], [100, 170, 30], [220, 220, 0], [175, 116, 175], [250, 0, 30], [165, 42, 42], [255, 77, 255], [0, 226, 252], [182, 182, 255], [0, 82, 0], [120, 166, 157], [110, 76, 0], [174, 57, 255], [199, 100, 0], [72, 0, 118], [255, 179, 240], [0, 125, 92], [209, 0, 151], [188, 208, 182], [0, 220, 176], [255, 99, 164], [92, 0, 73], [133, 129, 255], [78, 180, 255], [0, 228, 0], [174, 255, 243], [45, 89, 255], [134, 134, 103], [145, 148, 174], [255, 208, 186], [197, 226, 255], [171, 134, 1], [109, 63, 54], [207, 138, 255], [151, 0, 95], [9, 80, 61], [84, 105, 51], [74, 65, 105], [166, 196, 102], [208, 195, 210], [255, 109, 65], [0, 143, 149], [179, 0, 194], [209, 99, 106], [5, 121, 0], [227, 255, 205], [147, 186, 208], [153, 69, 1], [3, 95, 161], [163, 255, 0], [119, 0, 170], [0, 182, 199], [0, 165, 120], [183, 130, 88], [95, 32, 0], [130, 114, 135], [110, 129, 133], [166, 74, 118], [219, 142, 185], [79, 210, 114], [178, 90, 62], [65, 70, 15], [127, 167, 115], [59, 105, 106], [142, 108, 45], [196, 172, 0], [95, 54, 80], [128, 76, 255], [201, 57, 1], [246, 0, 122], [191, 162, 208], [255, 255, 128], [147, 211, 203], [150, 100, 100], [168, 171, 172], [146, 112, 198], [210, 170, 100], [92, 136, 89], [218, 88, 184], [241, 129, 0], [217, 17, 255], [124, 74, 181], [70, 70, 70], [255, 228, 255], [154, 208, 0], [193, 0, 92], [76, 91, 113], [255, 180, 195], [106, 154, 176], [230, 150, 140], [60, 143, 255], [128, 64, 128], [92, 82, 55], [254, 212, 124], [73, 77, 174], [255, 160, 98], [255, 255, 255], [104, 84, 109], [169, 164, 131], [225, 199, 255], [137, 54, 74], [135, 158, 223], [7, 246, 231], [107, 255, 200], [58, 41, 149], [183, 121, 142], [255, 73, 97], [107, 142, 35], [190, 153, 153], [146, 139, 141], [70, 130, 180], [134, 199, 156], [209, 226, 140], [96, 36, 108], [96, 96, 96], [64, 170, 64], [152, 251, 152], [208, 229, 228], [206, 186, 171], [152, 161, 64], [116, 112, 0], [0, 114, 143], [102, 102, 156], [250, 141, 255]], 'thing_dataset_id_to_contiguous_id': {1: 0, 2: 1, 3: 2, 4: 3, 5: 4, 6: 5, 7: 6, 8: 7, 9: 8, 10: 9, 11: 10, 13: 11, 14: 12, 15: 13, 16: 14, 17: 15, 18: 16, 19: 17, 20: 18, 21: 19, 22: 20, 23: 21, 24: 22, 25: 23, 27: 24, 28: 25, 31: 26, 32: 27, 33: 28, 34: 29, 35: 30, 36: 31, 37: 32, 38: 33, 39: 34, 40: 35, 41: 36, 42: 37, 43: 38, 44: 39, 46: 40, 47: 41, 48: 42, 49: 43, 50: 44, 51: 45, 52: 46, 53: 47, 54: 48, 55: 49, 56: 50, 57: 51, 58: 52, 59: 53, 60: 54, 61: 55, 62: 56, 63: 57, 64: 58, 65: 59, 67: 60, 70: 61, 72: 62, 73: 63, 74: 64, 75: 65, 76: 66, 77: 67, 78: 68, 79: 69, 80: 70, 81: 71, 82: 72, 84: 73, 85: 74, 86: 75, 87: 76, 88: 77, 89: 78, 90: 79}}", "loop_range": [35, 39], "post_loop_line": 41} {"idx": 3, "scratchpad_format": "def _merge(a, aux, lo, mid, hi):\n i = lo # [STATE] i = 0 [/STATE]\n j = mid + 1 # [STATE] j = 4 [/STATE]\n\n for k in range(lo, hi + 1): # [STATE] k = 0 [/STATE] [STATE] k = 1 [/STATE] [STATE] k = 2 [/STATE] [STATE] k = 3 [/STATE] [STATE] k = 4 [/STATE] [STATE] k = 5 [/STATE] [STATE] k = 6 [/STATE] [STATE] k = 7 [/STATE]\n aux[k] = a[k] # [STATE] aux = [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 4, 5, 6, 7, 0, 0, 0, 0, 0, 0, 0, 0] [/STATE] [STATE] aux = [1, 2, 4, 4, 5, 6, 7, 23, 0, 0, 0, 0, 0, 0, 0] [/STATE]\n\n for k in range(lo, hi + 1): # [STATE] k = 0 [/STATE] [STATE] k = 1 [/STATE] [STATE] k = 2 [/STATE] [STATE] k = 3 [/STATE] [STATE] k = 4 [/STATE] [STATE] k = 5 [/STATE] [STATE] k = 6 [/STATE] [STATE] k = 7 [/STATE]\n if i > mid:\n a[k] = aux[j]\n j += 1 # [STATE] j = 5 [/STATE] [STATE] j = 6 [/STATE] [STATE] j = 7 [/STATE] [STATE] j = 8 [/STATE]\n elif j > hi:\n a[k] = aux[i]\n i += 1\n elif util.less(aux[i], aux[j]):\n a[k] = aux[i]\n i += 1 # [STATE] i = 1 [/STATE] [STATE] i = 2 [/STATE] [STATE] i = 3 [/STATE] [STATE] i = 4 [/STATE]\n else:\n a[k] = aux[j]\n j += 1\n\n_merge([1, 2, 4, 4, 5, 6, 7, 23, 8, 9, 20, 11, 13, 34, 66], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 0, 3, 7)", "loop_code": "1: def _merge(a, aux, lo, mid, hi):\n2: i = lo\n3: j = mid + 1\n4:\n5: for k in range(lo, hi + 1):\n6: aux[k] = a[k]\n7:\n8: for k in range(lo, hi + 1):\n9: if i > mid:\n10: a[k] = aux[j]\n11: j += 1\n12: elif j > hi:\n13: a[k] = aux[i]\n14: i += 1\n15: elif util.less(aux[i], aux[j]):\n16: a[k] = aux[i]\n17: i += 1\n18: else:\n19: a[k] = aux[j]\n20: j += 1\n21:\n22: _merge([1, 2, 4, 4, 5, 6, 7, 23, 8, 9, 20, 11, 13, 34, 66], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 0, 3, 7)", "question": "What is the value of 'k' in line 8 after executing '_merge([1, 2, 4, 4, 5, 6, 7, 23, 8, 9, 20, 11, 13, 34, 66], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 0, 3, 7)'?", "answer": "3", "variable_assignment": "k = 3", "loop_range": [5, 6], "post_loop_line": 8} {"idx": 4, "scratchpad_format": "def join_options(options):\n \"\"\"Given a list of option strings this joins them in the most appropriate\n way and returns them in the form ``(formatted_string,\n any_prefix_is_slash)`` where the second item in the tuple is a flag that\n indicates if any of the option prefixes was a slash.\n \"\"\"\n rv = [] # [STATE] rv = [] [/STATE]\n any_prefix_is_slash = False # [STATE] any_prefix_is_slash = False [/STATE]\n for opt in options: # [STATE] opt = '--help' [/STATE]\n prefix = split_opt(opt)[0] # [STATE] prefix = '--' [/STATE]\n if prefix == '/':\n any_prefix_is_slash = True\n rv.append((len(prefix), opt)) # [STATE] rv = [(2, '--help')] [/STATE]\n\n rv.sort(key=lambda x: x[0])\n\n rv = ', '.join(x[1] for x in rv) # [STATE] rv = '--help' [/STATE]\n return rv, any_prefix_is_slash\n\njoin_options(['--help'])", "loop_code": "1: def join_options(options):\n2: \"\"\"Given a list of option strings this joins them in the most appropriate\n3: way and returns them in the form ``(formatted_string,\n4: any_prefix_is_slash)`` where the second item in the tuple is a flag that\n5: indicates if any of the option prefixes was a slash.\n6: \"\"\"\n7: rv = []\n8: any_prefix_is_slash = False\n9: for opt in options:\n10: prefix = split_opt(opt)[0]\n11: if prefix == '/':\n12: any_prefix_is_slash = True\n13: rv.append((len(prefix), opt))\n14:\n15: rv.sort(key=lambda x: x[0])\n16:\n17: rv = ', '.join(x[1] for x in rv)\n18: return rv, any_prefix_is_slash\n19:\n20: join_options(['--help'])", "question": "What is the value of 'rv' in line 17 after executing 'join_options(['--help'])'?", "answer": "'--help'", "variable_assignment": "rv = '--help'", "loop_range": [9, 13], "post_loop_line": 17} {"idx": 5, "scratchpad_format": "def which(exe=None):\n \"\"\"\n Python clone of /usr/bin/which\n \"\"\"\n\n if not exe:\n log.error(\"No executable was passed to be searched by salt.utils.path.which()\")\n return None\n\n ## define some utilities (we use closures here because our predecessor used them)\n def is_executable_common(path): # [STATE] is_executable_common = .is_executable_common at 0x7f27d3207c10> [/STATE]\n \"\"\"\n This returns truth if posixy semantics (which python simulates on\n windows) states that this is executable.\n \"\"\"\n return os.path.isfile(path) and os.access(path, os.X_OK)\n\n def resolve(path): # [STATE] resolve = .resolve at 0x7f27d3207820> [/STATE]\n \"\"\"\n This will take a path and recursively follow the link until we get to a\n real file.\n \"\"\"\n while os.path.islink(path):\n res = readlink(path)\n\n # if the link points to a relative target, then convert it to an\n # absolute path relative to the original path\n if not os.path.isabs(res):\n directory, _ = os.path.split(path)\n res = join(directory, res)\n path = res\n return path\n\n # windows-only\n def has_executable_ext(path, ext_membership): # [STATE] has_executable_ext = .has_executable_ext at 0x7f27d31c20d0> [/STATE]\n \"\"\"\n Extract the extension from the specified path, lowercase it so we\n can be insensitive, and then check it against the available exts.\n \"\"\"\n p, ext = os.path.splitext(path)\n return ext.lower() in ext_membership\n\n ## prepare related variables from the environment\n res = salt.utils.stringutils.to_unicode(os.environ.get(\"PATH\", \"\")) # [STATE] res = '/home/XXX/.gdrive-downloader:/local/arise/XXX/miniforge3/bin:/home/XXX/.gvm/pkgsets/go1.19.1/global/bin:/home/XXX/.gvm/gos/go1.19.1/bin:/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin:/home/XXX/.gvm/bin:/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin:/local/rcs/XXX/miniforge3/condabin:/home/XXX/.gdrive-downloader:/local/arise/XXX/miniforge3/bin:/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/XXX/.local/bin:/home/XXX/.local/bin' [/STATE]\n system_path = res.split(os.pathsep) # [STATE] system_path = ['/home/XXX/.gdrive-downloader', '/local/arise/XXX/miniforge3/bin', '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin', '/home/XXX/.gvm/gos/go1.19.1/bin', '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin', '/home/XXX/.gvm/bin', '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin', '/local/rcs/XXX/miniforge3/condabin', '/home/XXX/.gdrive-downloader', '/local/arise/XXX/miniforge3/bin', '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli', '/usr/local/sbin', '/usr/local/bin', '/usr/sbin', '/usr/bin', '/sbin', '/bin', '/usr/games', '/usr/local/games', '/snap/bin', '/home/XXX/.local/bin', '/home/XXX/.local/bin'] [/STATE]\n\n # add some reasonable defaults in case someone's PATH is busted\n if not salt.utils.platform.is_windows():\n res = set(system_path) # [STATE] res = {'/usr/games', '/sbin', '/home/XXX/.gvm/gos/go1.19.1/bin', '/home/XXX/.gvm/bin', '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin', '/home/XXX/.local/bin', '/snap/bin', '/usr/bin', '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli', '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin', '/bin', '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin', '/usr/local/games', '/usr/local/sbin', '/home/XXX/.gdrive-downloader', '/local/rcs/XXX/miniforge3/condabin', '/local/arise/XXX/miniforge3/bin', '/usr/sbin', '/usr/local/bin'} [/STATE]\n extended_path = [ # [STATE] extended_path = ['/sbin', '/bin', '/usr/sbin', '/usr/bin', '/usr/local/sbin', '/usr/local/bin'] [/STATE]\n \"/sbin\",\n \"/bin\",\n \"/usr/sbin\",\n \"/usr/bin\",\n \"/usr/local/sbin\",\n \"/usr/local/bin\",\n ]\n system_path.extend([p for p in extended_path if p not in res])\n\n ## now to define the semantics of what's considered executable on a given platform\n if salt.utils.platform.is_windows():\n # executable semantics on windows requires us to search PATHEXT\n res = salt.utils.stringutils.to_str(os.environ.get(\"PATHEXT\", \".EXE\"))\n\n # generate two variables, one of them for O(n) searches (but ordered)\n # and another for O(1) searches. the previous guy was trying to use\n # memoization with a function that has no arguments, this provides\n # the exact same benefit\n pathext = res.split(os.pathsep)\n res = {ext.lower() for ext in pathext}\n\n # check if our caller already specified a valid extension as then we don't need to match it\n _, ext = os.path.splitext(exe)\n if ext.lower() in res:\n pathext = [\"\"]\n\n is_executable = is_executable_common\n\n # The specified extension isn't valid, so we just assume it's part of the\n # filename and proceed to walk the pathext list\n else:\n is_executable = lambda path, membership=res: is_executable_common(\n path\n ) and has_executable_ext(path, membership)\n\n else:\n # in posix, there's no such thing as file extensions..only zuul\n pathext = [\"\"] # [STATE] pathext = [''] [/STATE]\n\n # executable semantics are pretty simple on reasonable platforms...\n is_executable = is_executable_common # [STATE] is_executable = .is_executable_common at 0x7f27d3207c10> [/STATE]\n\n ## search for the executable\n\n # check to see if the full path was specified as then we don't need\n # to actually walk the system_path for any reason\n if is_executable(exe):\n return exe\n\n # now to search through our system_path\n for path in system_path: # [STATE] path = '/home/XXX/.gdrive-downloader' [/STATE] [STATE] path = '/local/arise/XXX/miniforge3/bin' [/STATE] [STATE] path = '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin' [/STATE] [STATE] path = '/home/XXX/.gvm/gos/go1.19.1/bin' [/STATE] [STATE] path = '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin' [/STATE] [STATE] path = '/home/XXX/.gvm/bin' [/STATE] [STATE] path = '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin' [/STATE] [STATE] path = '/local/rcs/XXX/miniforge3/condabin' [/STATE] [STATE] path = '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli' [/STATE] [STATE] path = '/usr/local/sbin' [/STATE] [STATE] path = '/usr/local/bin' [/STATE] [STATE] path = '/usr/sbin' [/STATE] [STATE] path = '/usr/bin' [/STATE]\n p = join(path, exe) # [STATE] p = '/home/XXX/.gdrive-downloader/true' [/STATE] [STATE] p = '/local/arise/XXX/miniforge3/bin/true' [/STATE] [STATE] p = '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin/true' [/STATE] [STATE] p = '/home/XXX/.gvm/gos/go1.19.1/bin/true' [/STATE] [STATE] p = '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin/true' [/STATE] [STATE] p = '/home/XXX/.gvm/bin/true' [/STATE] [STATE] p = '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin/true' [/STATE] [STATE] p = '/local/rcs/XXX/miniforge3/condabin/true' [/STATE] [STATE] p = '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli/true' [/STATE] [STATE] p = '/usr/local/sbin/true' [/STATE] [STATE] p = '/usr/local/bin/true' [/STATE] [STATE] p = '/usr/sbin/true' [/STATE] [STATE] p = '/usr/bin/true' [/STATE]\n\n # iterate through all extensions to see which one is executable\n for ext in pathext: # [STATE] ext = '' [/STATE]\n pext = p + ext # [STATE] pext = '/home/XXX/.gdrive-downloader/true' [/STATE] [STATE] pext = '/local/arise/XXX/miniforge3/bin/true' [/STATE] [STATE] pext = '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin/true' [/STATE] [STATE] pext = '/home/XXX/.gvm/gos/go1.19.1/bin/true' [/STATE] [STATE] pext = '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin/true' [/STATE] [STATE] pext = '/home/XXX/.gvm/bin/true' [/STATE] [STATE] pext = '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin/true' [/STATE] [STATE] pext = '/local/rcs/XXX/miniforge3/condabin/true' [/STATE] [STATE] pext = '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli/true' [/STATE] [STATE] pext = '/usr/local/sbin/true' [/STATE] [STATE] pext = '/usr/local/bin/true' [/STATE] [STATE] pext = '/usr/sbin/true' [/STATE] [STATE] pext = '/usr/bin/true' [/STATE]\n rp = resolve(pext) # [STATE] rp = '/home/XXX/.gdrive-downloader/true' [/STATE] [STATE] rp = '/local/arise/XXX/miniforge3/bin/true' [/STATE] [STATE] rp = '/home/XXX/.gvm/pkgsets/go1.19.1/global/bin/true' [/STATE] [STATE] rp = '/home/XXX/.gvm/gos/go1.19.1/bin/true' [/STATE] [STATE] rp = '/home/XXX/.gvm/pkgsets/go1.19.1/global/overlay/bin/true' [/STATE] [STATE] rp = '/home/XXX/.gvm/bin/true' [/STATE] [STATE] rp = '/local/rcs/XXX/miniforge3/envs/saltstack+salt/bin/true' [/STATE] [STATE] rp = '/local/rcs/XXX/miniforge3/condabin/true' [/STATE] [STATE] rp = '/home/XXX/.vscode-server/cli/servers/Stable-31c37ee8f63491495ac49e43b8544550fbae4533/server/bin/remote-cli/true' [/STATE] [STATE] rp = '/usr/local/sbin/true' [/STATE] [STATE] rp = '/usr/local/bin/true' [/STATE] [STATE] rp = '/usr/sbin/true' [/STATE] [STATE] rp = '/usr/bin/true' [/STATE]\n if is_executable(rp):\n return p + ext\n continue\n continue\n\n ## if something was executable, we should've found it already...\n log.trace(\n \"'%s' could not be found in the following search path: '%s'\", exe, system_path\n )\n return None\n\nwhich('true')", "loop_code": "1: def which(exe=None):\n2: \"\"\"\n3: Python clone of /usr/bin/which\n4: \"\"\"\n5:\n6: if not exe:\n7: log.error(\"No executable was passed to be searched by salt.utils.path.which()\")\n8: return None\n9:\n10: ## define some utilities (we use closures here because our predecessor used them)\n11: def is_executable_common(path):\n12: \"\"\"\n13: This returns truth if posixy semantics (which python simulates on\n14: windows) states that this is executable.\n15: \"\"\"\n16: return os.path.isfile(path) and os.access(path, os.X_OK)\n17:\n18: def resolve(path):\n19: \"\"\"\n20: This will take a path and recursively follow the link until we get to a\n21: real file.\n22: \"\"\"\n23: while os.path.islink(path):\n24: res = readlink(path)\n25:\n26: # if the link points to a relative target, then convert it to an\n27: # absolute path relative to the original path\n28: if not os.path.isabs(res):\n29: directory, _ = os.path.split(path)\n30: res = join(directory, res)\n31: path = res\n32: return path\n33:\n34: # windows-only\n35: def has_executable_ext(path, ext_membership):\n36: \"\"\"\n37: Extract the extension from the specified path, lowercase it so we\n38: can be insensitive, and then check it against the available exts.\n39: \"\"\"\n40: p, ext = os.path.splitext(path)\n41: return ext.lower() in ext_membership\n42:\n43: ## prepare related variables from the environment\n44: res = salt.utils.stringutils.to_unicode(os.environ.get(\"PATH\", \"\"))\n45: system_path = res.split(os.pathsep)\n46:\n47: # add some reasonable defaults in case someone's PATH is busted\n48: if not salt.utils.platform.is_windows():\n49: res = set(system_path)\n50: extended_path = [\n51: \"/sbin\",\n52: \"/bin\",\n53: \"/usr/sbin\",\n54: \"/usr/bin\",\n55: \"/usr/local/sbin\",\n56: \"/usr/local/bin\",\n57: ]\n58: system_path.extend([p for p in extended_path if p not in res])\n59:\n60: ## now to define the semantics of what's considered executable on a given platform\n61: if salt.utils.platform.is_windows():\n62: # executable semantics on windows requires us to search PATHEXT\n63: res = salt.utils.stringutils.to_str(os.environ.get(\"PATHEXT\", \".EXE\"))\n64:\n65: # generate two variables, one of them for O(n) searches (but ordered)\n66: # and another for O(1) searches. the previous guy was trying to use\n67: # memoization with a function that has no arguments, this provides\n68: # the exact same benefit\n69: pathext = res.split(os.pathsep)\n70: res = {ext.lower() for ext in pathext}\n71:\n72: # check if our caller already specified a valid extension as then we don't need to match it\n73: _, ext = os.path.splitext(exe)\n74: if ext.lower() in res:\n75: pathext = [\"\"]\n76:\n77: is_executable = is_executable_common\n78:\n79: # The specified extension isn't valid, so we just assume it's part of the\n80: # filename and proceed to walk the pathext list\n81: else:\n82: is_executable = lambda path, membership=res: is_executable_common(\n83: path\n84: ) and has_executable_ext(path, membership)\n85:\n86: else:\n87: # in posix, there's no such thing as file extensions..only zuul\n88: pathext = [\"\"]\n89:\n90: # executable semantics are pretty simple on reasonable platforms...\n91: is_executable = is_executable_common\n92:\n93: ## search for the executable\n94:\n95: # check to see if the full path was specified as then we don't need\n96: # to actually walk the system_path for any reason\n97: if is_executable(exe):\n98: return exe\n99:\n100: # now to search through our system_path\n101: for path in system_path:\n102: p = join(path, exe)\n103:\n104: # iterate through all extensions to see which one is executable\n105: for ext in pathext:\n106: pext = p + ext\n107: rp = resolve(pext)\n108: if is_executable(rp):\n109: return p + ext\n110: continue\n111: continue\n112:\n113: ## if something was executable, we should've found it already...\n114: log.trace(\n115: \"'%s' could not be found in the following search path: '%s'\", exe, system_path\n116: )\n117: return None\n118:\n119: which('true')", "question": "What is the value of 'has_executable_ext' in line 35 after executing 'which('true')'?", "answer": ".has_executable_ext at 0x7f27d31c20d0>", "variable_assignment": "has_executable_ext = .has_executable_ext at 0x7f27d31c20d0>", "loop_range": [23, 31], "post_loop_line": 35} {"idx": 6, "scratchpad_format": "def _remove_comments_inline(text):\n \"\"\"Removes the comments from the string 'text' and ignores % inside \\\\url{}.\"\"\"\n if 'auto-ignore' in text:\n return text\n if text.lstrip(' ').lstrip('\\t').startswith('%'):\n return ''\n\n url_pattern = r'\\\\url\\{(?>[^{}]|(?R))*\\}' # [STATE] url_pattern = '\\\\\\\\url\\\\{(?>[^{}]|(?R))*\\\\}' [/STATE]\n\n def remove_comments(segment): # [STATE] remove_comments = .remove_comments at 0x7f185616f280> [/STATE]\n \"\"\"Remove comments from a segment of text.\"\"\"\n if segment.lstrip().startswith('%'):\n return ''\n match = regex.search(r'(?[^{}]|(?R))*\\}'\n9:\n10: def remove_comments(segment):\n11: \"\"\"Remove comments from a segment of text.\"\"\"\n12: if segment.lstrip().startswith('%'):\n13: return ''\n14: match = regex.search(r'(?)?()?[\\s%]*\\}\n filename_regex = path_prefix_regex + basename_regex # [STATE] filename_regex = '((/)?to/)?img(\\\\.ext)?' [/STATE]\n\n # Some files 'path/to/file' are referenced in tex as './path/to/file' thus\n # adds prefix for relative paths starting with './' or '.\\' to regex search.\n filename_regex = r'(.' + os.sep + r')?' + filename_regex # [STATE] filename_regex = '(./)?((/)?to/)?img(\\\\.ext)?' [/STATE]\n\n # Pads with braces and optional whitespace/comment characters.\n patn = r'\\{{[\\s%]*{}[\\s%]*\\}}'.format(filename_regex) # [STATE] patn = '\\\\{[\\\\s%]*(./)?((/)?to/)?img(\\\\.ext)?[\\\\s%]*\\\\}' [/STATE]\n # Picture references in LaTeX are allowed to be in different cases.\n return regex.search(patn, contents, regex.IGNORECASE)\n\n_search_reference('to/img.ext', '{long/path/to/img}', False)", "loop_code": "1: def _search_reference(filename, contents, strict=False):\n2: \"\"\"Returns a match object if filename is referenced in contents, and None otherwise.\n3:\n4: If not strict mode, path prefix and extension are optional.\n5: \"\"\"\n6: if strict:\n7: # regex pattern for strict=True for path/to/img.ext:\n8: # \\{[\\s%]*path/to/img\\.ext[\\s%]*\\}\n9: filename_regex = filename.replace('.', r'\\.')\n10: else:\n11: filename_path = Path(filename)\n12:\n13: # make extension optional\n14: root, extension = filename_path.stem, filename_path.suffix\n15: basename_regex = '{}({})?'.format(\n16: regex.escape(root), regex.escape(extension)\n17: )\n18:\n19: # iterate through parent fragments to make path prefix optional\n20: path_prefix_regex = ''\n21: for fragment in reversed(filename_path.parents):\n22: if fragment.name == '.':\n23: continue\n24: fragment = regex.escape(fragment.name)\n25: path_prefix_regex = '({}{}{})?'.format(\n26: path_prefix_regex, fragment, os.sep\n27: )\n28:\n29: # Regex pattern for strict=True for path/to/img.ext:\n30: # \\{[\\s%]*()?()?[\\s%]*\\}\n31: filename_regex = path_prefix_regex + basename_regex\n32:\n33: # Some files 'path/to/file' are referenced in tex as './path/to/file' thus\n34: # adds prefix for relative paths starting with './' or '.\\' to regex search.\n35: filename_regex = r'(.' + os.sep + r')?' + filename_regex\n36:\n37: # Pads with braces and optional whitespace/comment characters.\n38: patn = r'\\{{[\\s%]*{}[\\s%]*\\}}'.format(filename_regex)\n39: # Picture references in LaTeX are allowed to be in different cases.\n40: return regex.search(patn, contents, regex.IGNORECASE)\n41:\n42: _search_reference('to/img.ext', '{long/path/to/img}', False)", "question": "What is the value of 'filename_regex' in line 31 after executing '_search_reference('to/img.ext', '{long/path/to/img}', False)'?", "answer": "'((/)?to/)?img(\\\\.ext)?'", "variable_assignment": "filename_regex = '((/)?to/)?img(\\\\.ext)?'", "loop_range": [21, 27], "post_loop_line": 31} {"idx": 8, "scratchpad_format": "def run_arxiv_cleaner(parameters):\n \"\"\"Core of the code, runs the actual arXiv cleaner.\"\"\"\n\n files_to_delete = [ # [STATE] files_to_delete = ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$'] [/STATE]\n r'\\.aux$',\n r'\\.sh$',\n r'\\.blg$',\n r'\\.brf$',\n r'\\.log$',\n r'\\.out$',\n r'\\.ps$',\n r'\\.dvi$',\n r'\\.synctex.gz$',\n '~$',\n r'\\.backup$',\n r'\\.gitignore$',\n r'\\.DS_Store$',\n r'\\.svg$',\n r'^\\.idea',\n r'\\.dpth$',\n r'\\.md5$',\n r'\\.dep$',\n r'\\.auxlock$',\n r'\\.fls$',\n r'\\.fdb_latexmk$',\n ]\n\n if not parameters['keep_bib']:\n files_to_delete.append(r'\\.bib$') # [STATE] files_to_delete = ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'] [/STATE]\n\n parameters.update({ # [STATE] parameters = {'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False, 'to_delete': ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'], 'figures_to_copy_if_referenced': ['\\\\.png$', '\\\\.jpg$', '\\\\.jpeg$', '\\\\.pdf$']} [/STATE]\n 'to_delete': files_to_delete,\n 'figures_to_copy_if_referenced': [\n r'\\.png$',\n r'\\.jpg$',\n r'\\.jpeg$',\n r'\\.pdf$',\n ],\n })\n\n logging.info('Collecting file structure.')\n parameters['output_folder'] = _create_out_folder(parameters['input_folder']) # [STATE] parameters = {'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False, 'to_delete': ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'], 'figures_to_copy_if_referenced': ['\\\\.png$', '\\\\.jpg$', '\\\\.jpeg$', '\\\\.pdf$'], 'output_folder': '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv'} [/STATE]\n\n from_zip = parameters['input_folder'].endswith('.zip') # [STATE] from_zip = False [/STATE]\n tempdir_context = ( # [STATE] tempdir_context = {_exceptions=()} [/STATE]\n tempfile.TemporaryDirectory() if from_zip else contextlib.suppress()\n )\n\n with tempdir_context as tempdir: # [STATE] tempdir = None [/STATE]\n\n if from_zip:\n logging.info('Unzipping input folder.')\n shutil.unpack_archive(parameters['input_folder'], tempdir)\n parameters['input_folder'] = tempdir\n\n splits = _split_all_files(parameters) # [STATE] splits = {'all': ['main.bib', 'main.bbl', 'main.tex', 'main.aux', 'ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'in_root': ['main.bib', 'main.bbl', 'main.tex', 'main.aux'], 'not_in_root': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'to_copy_in_root': ['main.bbl', 'main.tex'], 'to_copy_not_in_root': ['figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt'], 'figures': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'tex_in_root': ['main.tex'], 'tex_not_in_root': ['figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex'], 'non_tex_in_root': ['main.bbl'], 'non_tex_not_in_root': ['figures/data_not_included.txt', 'figures/data_included.txt', 'not_included/figures/data_included.txt'], 'external_tikz_figures': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf'], 'svg_inkscape': []} [/STATE]\n\n logging.info('Reading all tex files')\n tex_contents = _read_all_tex_contents( # [STATE] tex_contents = {'main.tex': ['\\\\begin{document}\\n', 'Text\\n', '% Whole line comment\\n', '\\n', 'Text% Inline comment\\n', '\\\\begin{comment}\\n', 'This is an environment comment.\\n', '\\\\end{comment}\\n', '\\n', 'This is a percent \\\\%.\\n', '% Whole line comment without newline\\n', '\\\\includegraphics{images/im1_included.png}\\n', '%\\\\includegraphics{images/im_not_included}\\n', '\\\\includegraphics{images/im3_included.png}\\n', '\\\\includegraphics{%\\n', ' images/im4_included.png%\\n', ' }\\n', '\\\\includegraphics[width=.5\\\\linewidth]{%\\n', ' images/im5_included.jpg}\\n', '%\\\\includegraphics{%\\n', '% images/im4_not_included.png\\n', '% }\\n', '%\\\\includegraphics[width=.5\\\\linewidth]{%\\n', '% images/im5_not_included.jpg}\\n', '\\n', '% test whatever the path satrting with dot works when include graphics\\n', '\\\\includegraphics{./images/im3_included.png}\\n', '\\n', 'This line should\\\\mytodo{Do this later} not be separated\\n', '\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\n', 'Please remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\n', 'from this one.\\n', '\\n', '\\\\begin{mynote}\\n', ' This is a custom environment that could be excluded.\\n', '\\\\end{mynote}\\n', '\\n', '\\\\newif\\\\ifvar\\n', '\\n', '\\\\ifvar\\n', '\\\\if false\\n', '\\\\if false\\n', '\\\\if 0\\n', '\\\\iffalse\\n', '\\\\ifvar\\n', 'Text\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\n', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\n', 'hello test \\\\red{hello\\n', 'test \\\\red{hello}}\\n', 'test\\n', '\\n', '% content after this line should not be cleaned if \\\\end{document} is in a comment\\n', '\\n', '\\\\input{figures/figure_included.tex}\\n', '% \\\\input{figures/figure_not_included.tex}\\n', '\\n', '% Test for tikzpicture feature\\n', '% should be replaced\\n', '\\\\tikzsetnextfilename{test1}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test1};\\n', '\\\\end{tikzpicture}\\n', '\\n', '% should be replaced in included file\\n', '\\\\input{figures/figure_included.tikz}\\n', '\\n', '% should not be be replaced - no preceding tikzsetnextfilename command\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test3};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\tikzsetnextfilename{test_no_match}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test4};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\end{document}\\n'], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}\\n', '\\\\input{figures/figure_not_included_2.tex}\\n'], 'figures/figure_not_included_2.tex': [], 'figures/figure_included.tikz': ['\\ufeff\\\\tikzsetnextfilename{test2}\\n', '\\\\begin{tikzpicture}\\n', '\\\\node {root}\\n', 'child {node {left}}\\n', 'child {node {right}\\n', 'child {node {child}}\\n', 'child {node {child}}\\n', '};\\n', '\\\\end{tikzpicture}'], 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}\\n', '\\\\addplot{figures/data_included.txt}\\n']} [/STATE]\n splits['tex_in_root'] + splits['tex_not_in_root'], parameters\n )\n\n for tex_file in tex_contents: # [STATE] tex_file = 'main.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included_2.tex' [/STATE] [STATE] tex_file = 'figures/figure_included.tikz' [/STATE] [STATE] tex_file = 'figures/figure_included.tex' [/STATE]\n logging.info('Removing comments in file %s.', tex_file)\n tex_contents[tex_file] = _remove_comments_and_commands_to_delete( # [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}\\n', '\\\\input{figures/figure_not_included_2.tex}\\n'], 'figures/figure_not_included_2.tex': [], 'figures/figure_included.tikz': ['\\ufeff\\\\tikzsetnextfilename{test2}\\n', '\\\\begin{tikzpicture}\\n', '\\\\node {root}\\n', 'child {node {left}}\\n', 'child {node {right}\\n', 'child {node {child}}\\n', 'child {node {child}}\\n', '};\\n', '\\\\end{tikzpicture}'], 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}\\n', '\\\\addplot{figures/data_included.txt}\\n']} [/STATE] [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n', 'figures/figure_not_included_2.tex': [], 'figures/figure_included.tikz': ['\\ufeff\\\\tikzsetnextfilename{test2}\\n', '\\\\begin{tikzpicture}\\n', '\\\\node {root}\\n', 'child {node {left}}\\n', 'child {node {right}\\n', 'child {node {child}}\\n', 'child {node {child}}\\n', '};\\n', '\\\\end{tikzpicture}'], 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}\\n', '\\\\addplot{figures/data_included.txt}\\n']} [/STATE] [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n', 'figures/figure_not_included_2.tex': '', 'figures/figure_included.tikz': ['\\ufeff\\\\tikzsetnextfilename{test2}\\n', '\\\\begin{tikzpicture}\\n', '\\\\node {root}\\n', 'child {node {left}}\\n', 'child {node {right}\\n', 'child {node {child}}\\n', 'child {node {child}}\\n', '};\\n', '\\\\end{tikzpicture}'], 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}\\n', '\\\\addplot{figures/data_included.txt}\\n']} [/STATE] [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n', 'figures/figure_not_included_2.tex': '', 'figures/figure_included.tikz': '\\ufeff\\\\tikzsetnextfilename{test2}\\n\\\\begin{tikzpicture}\\n\\\\node {root}\\nchild {node {left}}\\nchild {node {right}\\nchild {node {child}}\\nchild {node {child}}\\n};\\n\\\\end{tikzpicture}\\n', 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}\\n', '\\\\addplot{figures/data_included.txt}\\n']} [/STATE] [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n', 'figures/figure_not_included_2.tex': '', 'figures/figure_included.tikz': '\\ufeff\\\\tikzsetnextfilename{test2}\\n\\\\begin{tikzpicture}\\n\\\\node {root}\\nchild {node {left}}\\nchild {node {right}\\nchild {node {child}}\\nchild {node {child}}\\n};\\n\\\\end{tikzpicture}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE]\n tex_contents[tex_file], parameters\n )\n\n for tex_file in tex_contents: # [STATE] tex_file = 'main.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included_2.tex' [/STATE] [STATE] tex_file = 'figures/figure_included.tikz' [/STATE] [STATE] tex_file = 'figures/figure_included.tex' [/STATE]\n logging.info('Replacing \\\\includesvg calls in file %s.', tex_file)\n tex_contents[tex_file] = _replace_includesvg(\n tex_contents[tex_file], splits['svg_inkscape']\n )\n\n for tex_file in tex_contents: # [STATE] tex_file = 'main.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included.tex' [/STATE] [STATE] tex_file = 'figures/figure_not_included_2.tex' [/STATE] [STATE] tex_file = 'figures/figure_included.tikz' [/STATE] [STATE] tex_file = 'figures/figure_included.tex' [/STATE]\n logging.info('Replacing Tikz Pictures in file %s.', tex_file)\n content = _replace_tikzpictures( # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\includegraphics{ext_tikz/test1.pdf}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE] [STATE] content = '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n' [/STATE] [STATE] content = '' [/STATE] [STATE] content = '\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}\\n' [/STATE] [STATE] content = '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n' [/STATE]\n tex_contents[tex_file], splits['external_tikz_figures']\n )\n # If file ends with '\\n' already, the split in last line would add an extra\n # '\\n', so we remove it.\n tex_contents[tex_file] = content.split('\\n') # [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': '\\\\addplot{figures/data_not_included.txt}\\n\\\\input{figures/figure_not_included_2.tex}\\n', 'figures/figure_not_included_2.tex': '', 'figures/figure_included.tikz': '\\ufeff\\\\tikzsetnextfilename{test2}\\n\\\\begin{tikzpicture}\\n\\\\node {root}\\nchild {node {left}}\\nchild {node {right}\\nchild {node {child}}\\nchild {node {child}}\\n};\\n\\\\end{tikzpicture}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': '', 'figures/figure_included.tikz': '\\ufeff\\\\tikzsetnextfilename{test2}\\n\\\\begin{tikzpicture}\\n\\\\node {root}\\nchild {node {left}}\\nchild {node {right}\\nchild {node {child}}\\nchild {node {child}}\\n};\\n\\\\end{tikzpicture}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': '\\ufeff\\\\tikzsetnextfilename{test2}\\n\\\\begin{tikzpicture}\\n\\\\node {root}\\nchild {node {left}}\\nchild {node {right}\\nchild {node {child}}\\nchild {node {child}}\\n};\\n\\\\end{tikzpicture}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': ['\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}', ''], 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': ['\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}', ''], 'figures/figure_included.tex': ['\\\\includegraphics{images/im2_included.jpg}', '\\\\addplot{figures/data_included.txt}', '']} [/STATE]\n\n _keep_only_referenced_tex(tex_contents, splits) # [STATE] splits = {'all': ['main.bib', 'main.bbl', 'main.tex', 'main.aux', 'ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'in_root': ['main.bib', 'main.bbl', 'main.tex', 'main.aux'], 'not_in_root': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'to_copy_in_root': ['main.bbl', 'main.tex'], 'to_copy_not_in_root': ['figures/data_not_included.txt', 'figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex', 'figures/data_included.txt', 'not_included/figures/data_included.txt'], 'figures': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf', 'images/im4_included.png', 'images/im1.png', 'images/im4_not_included.png', 'images/im3_included.png', 'images/im2_included.jpg', 'images/im5_not_included.jpg', 'images/im5_included.jpg', 'images/im1_included.png', 'images/im_not_included.png', 'images/include/images/im3_included.png'], 'tex_in_root': ['main.tex'], 'tex_not_in_root': ['figures/figure_not_included.tex', 'figures/figure_not_included_2.tex', 'figures/figure_included.tikz', 'figures/figure_included.tex'], 'non_tex_in_root': ['main.bbl'], 'non_tex_not_in_root': ['figures/data_not_included.txt', 'figures/data_included.txt', 'not_included/figures/data_included.txt'], 'external_tikz_figures': ['ext_tikz/test2.pdf', 'ext_tikz/test1.pdf', 'ext_tikz/figure_not_included.pdf'], 'svg_inkscape': [], 'tex_to_copy': ['figures/figure_included.tex', 'figures/figure_included.tikz', 'main.tex']} [/STATE]\n _add_root_tex_files(splits)\n\n for tex_file in splits['tex_to_copy']: # [STATE] tex_file = 'figures/figure_included.tikz' [/STATE] [STATE] tex_file = 'main.tex' [/STATE]\n logging.info('Replacing patterns in file %s.', tex_file)\n content = '\\n'.join(tex_contents[tex_file]) # [STATE] content = '\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}\\n' [/STATE] [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\includegraphics{ext_tikz/test1.pdf}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n content = _find_and_replace_patterns(\n content, parameters.get('patterns_and_insertions', list())\n )\n tex_contents[tex_file] = content # [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': ['\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}', ''], 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': ['\\\\begin{document}', 'Text', '', 'Text%', '', '', 'This is a percent \\\\%.', '\\\\includegraphics{images/im1_included.png}', '\\\\includegraphics{images/im3_included.png}', '\\\\includegraphics{%', ' images/im4_included.png%', ' }', '\\\\includegraphics[width=.5\\\\linewidth]{%', ' images/im5_included.jpg}', '', '\\\\includegraphics{./images/im3_included.png}', '', 'This line should not be separated', '%', 'from this one.', '', '', '', '\\\\newif\\\\ifvar', '', '\\\\ifvar', '\\\\fi', '', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}', 'hello test hello', 'test hello', 'test', '', '', '\\\\input{figures/figure_included.tex}', '', '\\\\includegraphics{ext_tikz/test1.pdf}', '', '\\\\input{figures/figure_included.tikz}', '', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test3};', '\\\\end{tikzpicture}', '', '\\\\tikzsetnextfilename{test_no_match}', '\\\\begin{tikzpicture}', ' \\\\node (test) at (0,0) {Test4};', '\\\\end{tikzpicture}', '', '\\\\end{document}', ''], 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': '\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE] [STATE] tex_contents = {'main.tex': '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\includegraphics{ext_tikz/test1.pdf}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n', 'figures/figure_not_included.tex': ['\\\\addplot{figures/data_not_included.txt}', '\\\\input{figures/figure_not_included_2.tex}', ''], 'figures/figure_not_included_2.tex': [''], 'figures/figure_included.tikz': '\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}\\n', 'figures/figure_included.tex': '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n'} [/STATE]\n new_path = os.path.join(parameters['output_folder'], tex_file) # [STATE] new_path = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv/figures/figure_included.tex' [/STATE] [STATE] new_path = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv/figures/figure_included.tikz' [/STATE] [STATE] new_path = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv/main.tex' [/STATE]\n logging.info('Writing modified contents to %s.', new_path)\n _write_file_content(\n content,\n new_path,\n )\n\n full_content = '\\n'.join( # [STATE] full_content = '\\\\includegraphics{images/im2_included.jpg}\\n\\\\addplot{figures/data_included.txt}\\n\\n\\ufeff\\\\includegraphics{ext_tikz/test2.pdf}\\n\\n\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\includegraphics{ext_tikz/test1.pdf}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n ''.join(tex_contents[fn]) for fn in splits['tex_to_copy']\n )\n _copy_only_referenced_non_tex_not_in_root(parameters, full_content, splits)\n for non_tex_file in splits['non_tex_in_root']: # [STATE] non_tex_file = 'main.bbl' [/STATE]\n logging.info('Copying non-tex file %s.', non_tex_file)\n _copy_file(non_tex_file, parameters)\n\n _resize_and_copy_figures_if_referenced(parameters, full_content, splits)\n logging.info('Outputs written to %s', parameters['output_folder'])\n\nrun_arxiv_cleaner({'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False})", "loop_code": "1: def run_arxiv_cleaner(parameters):\n2: \"\"\"Core of the code, runs the actual arXiv cleaner.\"\"\"\n3:\n4: files_to_delete = [\n5: r'\\.aux$',\n6: r'\\.sh$',\n7: r'\\.blg$',\n8: r'\\.brf$',\n9: r'\\.log$',\n10: r'\\.out$',\n11: r'\\.ps$',\n12: r'\\.dvi$',\n13: r'\\.synctex.gz$',\n14: '~$',\n15: r'\\.backup$',\n16: r'\\.gitignore$',\n17: r'\\.DS_Store$',\n18: r'\\.svg$',\n19: r'^\\.idea',\n20: r'\\.dpth$',\n21: r'\\.md5$',\n22: r'\\.dep$',\n23: r'\\.auxlock$',\n24: r'\\.fls$',\n25: r'\\.fdb_latexmk$',\n26: ]\n27:\n28: if not parameters['keep_bib']:\n29: files_to_delete.append(r'\\.bib$')\n30:\n31: parameters.update({\n32: 'to_delete': files_to_delete,\n33: 'figures_to_copy_if_referenced': [\n34: r'\\.png$',\n35: r'\\.jpg$',\n36: r'\\.jpeg$',\n37: r'\\.pdf$',\n38: ],\n39: })\n40:\n41: logging.info('Collecting file structure.')\n42: parameters['output_folder'] = _create_out_folder(parameters['input_folder'])\n43:\n44: from_zip = parameters['input_folder'].endswith('.zip')\n45: tempdir_context = (\n46: tempfile.TemporaryDirectory() if from_zip else contextlib.suppress()\n47: )\n48:\n49: with tempdir_context as tempdir:\n50:\n51: if from_zip:\n52: logging.info('Unzipping input folder.')\n53: shutil.unpack_archive(parameters['input_folder'], tempdir)\n54: parameters['input_folder'] = tempdir\n55:\n56: splits = _split_all_files(parameters)\n57:\n58: logging.info('Reading all tex files')\n59: tex_contents = _read_all_tex_contents(\n60: splits['tex_in_root'] + splits['tex_not_in_root'], parameters\n61: )\n62:\n63: for tex_file in tex_contents:\n64: logging.info('Removing comments in file %s.', tex_file)\n65: tex_contents[tex_file] = _remove_comments_and_commands_to_delete(\n66: tex_contents[tex_file], parameters\n67: )\n68:\n69: for tex_file in tex_contents:\n70: logging.info('Replacing \\\\includesvg calls in file %s.', tex_file)\n71: tex_contents[tex_file] = _replace_includesvg(\n72: tex_contents[tex_file], splits['svg_inkscape']\n73: )\n74:\n75: for tex_file in tex_contents:\n76: logging.info('Replacing Tikz Pictures in file %s.', tex_file)\n77: content = _replace_tikzpictures(\n78: tex_contents[tex_file], splits['external_tikz_figures']\n79: )\n80: # If file ends with '\\n' already, the split in last line would add an extra\n81: # '\\n', so we remove it.\n82: tex_contents[tex_file] = content.split('\\n')\n83:\n84: _keep_only_referenced_tex(tex_contents, splits)\n85: _add_root_tex_files(splits)\n86:\n87: for tex_file in splits['tex_to_copy']:\n88: logging.info('Replacing patterns in file %s.', tex_file)\n89: content = '\\n'.join(tex_contents[tex_file])\n90: content = _find_and_replace_patterns(\n91: content, parameters.get('patterns_and_insertions', list())\n92: )\n93: tex_contents[tex_file] = content\n94: new_path = os.path.join(parameters['output_folder'], tex_file)\n95: logging.info('Writing modified contents to %s.', new_path)\n96: _write_file_content(\n97: content,\n98: new_path,\n99: )\n100:\n101: full_content = '\\n'.join(\n102: ''.join(tex_contents[fn]) for fn in splits['tex_to_copy']\n103: )\n104: _copy_only_referenced_non_tex_not_in_root(parameters, full_content, splits)\n105: for non_tex_file in splits['non_tex_in_root']:\n106: logging.info('Copying non-tex file %s.', non_tex_file)\n107: _copy_file(non_tex_file, parameters)\n108:\n109: _resize_and_copy_figures_if_referenced(parameters, full_content, splits)\n110: logging.info('Outputs written to %s', parameters['output_folder'])\n111:\n112: run_arxiv_cleaner({'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False})", "question": "What is the value of 'tex_file' in line 75 after executing 'run_arxiv_cleaner({'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False})'?", "answer": "'figures/figure_included.tikz'", "variable_assignment": "tex_file = 'figures/figure_included.tikz'", "loop_range": [69, 73], "post_loop_line": 75} {"idx": 9, "scratchpad_format": "def _remove_comments_and_commands_to_delete(content, parameters):\n \"\"\"Erases all LaTeX comments in the content, and writes it.\"\"\"\n content = [_remove_comments_inline(line) for line in content] # [STATE] content = ['\\\\begin{document}\\n', 'Text\\n', '', '\\n', 'Text%\\n', '\\\\begin{comment}\\n', 'This is an environment comment.\\n', '\\\\end{comment}\\n', '\\n', 'This is a percent \\\\%.\\n', '', '\\\\includegraphics{images/im1_included.png}\\n', '', '\\\\includegraphics{images/im3_included.png}\\n', '\\\\includegraphics{%\\n', ' images/im4_included.png%\\n', ' }\\n', '\\\\includegraphics[width=.5\\\\linewidth]{%\\n', ' images/im5_included.jpg}\\n', '', '', '', '', '', '\\n', '', '\\\\includegraphics{./images/im3_included.png}\\n', '\\n', 'This line should\\\\mytodo{Do this later} not be separated\\n', '\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\n', 'Please remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\n', 'from this one.\\n', '\\n', '\\\\begin{mynote}\\n', ' This is a custom environment that could be excluded.\\n', '\\\\end{mynote}\\n', '\\n', '\\\\newif\\\\ifvar\\n', '\\n', '\\\\ifvar\\n', '\\\\if false\\n', '\\\\if false\\n', '\\\\if 0\\n', '\\\\iffalse\\n', '\\\\ifvar\\n', 'Text\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\n', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\n', 'hello test \\\\red{hello\\n', 'test \\\\red{hello}}\\n', 'test\\n', '\\n', '', '\\n', '\\\\input{figures/figure_included.tex}\\n', '', '\\n', '', '', '\\\\tikzsetnextfilename{test1}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test1};\\n', '\\\\end{tikzpicture}\\n', '\\n', '', '\\\\input{figures/figure_included.tikz}\\n', '\\n', '', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test3};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\tikzsetnextfilename{test_no_match}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test4};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\end{document}\\n'] [/STATE]\n content = _remove_environment(''.join(content), 'comment') # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should\\\\mytodo{Do this later} not be separated\\n\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\nPlease remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\nfrom this one.\\n\\n\\\\begin{mynote}\\n This is a custom environment that could be excluded.\\n\\\\end{mynote}\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\if false\\n\\\\if false\\n\\\\if 0\\n\\\\iffalse\\n\\\\ifvar\\nText\\n\\\\fi\\n\\\\fi\\n\\\\fi\\n\\\\fi\\n\\\\fi\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test \\\\red{hello\\ntest \\\\red{hello}}\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n content = _remove_iffalse_block(content) # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should\\\\mytodo{Do this later} not be separated\\n\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\nPlease remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\nfrom this one.\\n\\n\\\\begin{mynote}\\n This is a custom environment that could be excluded.\\n\\\\end{mynote}\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test \\\\red{hello\\ntest \\\\red{hello}}\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n for environment in parameters.get('environments_to_delete', []): # [STATE] environment = 'mynote' [/STATE]\n content = _remove_environment(content, environment) # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should\\\\mytodo{Do this later} not be separated\\n\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\nPlease remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test \\\\red{hello\\ntest \\\\red{hello}}\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n for command in parameters.get('commands_only_to_delete', []): # [STATE] command = 'red' [/STATE]\n content = _remove_command(content, command, True) # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should\\\\mytodo{Do this later} not be separated\\n\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\nPlease remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n for command in parameters['commands_to_delete']: # [STATE] command = 'mytodo' [/STATE]\n content = _remove_command(content, command, False) # [STATE] content = '\\\\begin{document}\\nText\\n\\nText%\\n\\n\\nThis is a percent \\\\%.\\n\\\\includegraphics{images/im1_included.png}\\n\\\\includegraphics{images/im3_included.png}\\n\\\\includegraphics{%\\n images/im4_included.png%\\n }\\n\\\\includegraphics[width=.5\\\\linewidth]{%\\n images/im5_included.jpg}\\n\\n\\\\includegraphics{./images/im3_included.png}\\n\\nThis line should not be separated\\n%\\nfrom this one.\\n\\n\\n\\n\\\\newif\\\\ifvar\\n\\n\\\\ifvar\\n\\\\fi\\n\\n\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\nhello test hello\\ntest hello\\ntest\\n\\n\\n\\\\input{figures/figure_included.tex}\\n\\n\\\\tikzsetnextfilename{test1}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test1};\\n\\\\end{tikzpicture}\\n\\n\\\\input{figures/figure_included.tikz}\\n\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test3};\\n\\\\end{tikzpicture}\\n\\n\\\\tikzsetnextfilename{test_no_match}\\n\\\\begin{tikzpicture}\\n \\\\node (test) at (0,0) {Test4};\\n\\\\end{tikzpicture}\\n\\n\\\\end{document}\\n' [/STATE]\n return content\n\n_remove_comments_and_commands_to_delete(['\\\\begin{document}\\n', 'Text\\n', '% Whole line comment\\n', '\\n', 'Text% Inline comment\\n', '\\\\begin{comment}\\n', 'This is an environment comment.\\n', '\\\\end{comment}\\n', '\\n', 'This is a percent \\\\%.\\n', '% Whole line comment without newline\\n', '\\\\includegraphics{images/im1_included.png}\\n', '%\\\\includegraphics{images/im_not_included}\\n', '\\\\includegraphics{images/im3_included.png}\\n', '\\\\includegraphics{%\\n', ' images/im4_included.png%\\n', ' }\\n', '\\\\includegraphics[width=.5\\\\linewidth]{%\\n', ' images/im5_included.jpg}\\n', '%\\\\includegraphics{%\\n', '% images/im4_not_included.png\\n', '% }\\n', '%\\\\includegraphics[width=.5\\\\linewidth]{%\\n', '% images/im5_not_included.jpg}\\n', '\\n', '% test whatever the path satrting with dot works when include graphics\\n', '\\\\includegraphics{./images/im3_included.png}\\n', '\\n', 'This line should\\\\mytodo{Do this later} not be separated\\n', '\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\n', 'Please remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\n', 'from this one.\\n', '\\n', '\\\\begin{mynote}\\n', ' This is a custom environment that could be excluded.\\n', '\\\\end{mynote}\\n', '\\n', '\\\\newif\\\\ifvar\\n', '\\n', '\\\\ifvar\\n', '\\\\if false\\n', '\\\\if false\\n', '\\\\if 0\\n', '\\\\iffalse\\n', '\\\\ifvar\\n', 'Text\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\n', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\n', 'hello test \\\\red{hello\\n', 'test \\\\red{hello}}\\n', 'test\\n', '\\n', '% content after this line should not be cleaned if \\\\end{document} is in a comment\\n', '\\n', '\\\\input{figures/figure_included.tex}\\n', '% \\\\input{figures/figure_not_included.tex}\\n', '\\n', '% Test for tikzpicture feature\\n', '% should be replaced\\n', '\\\\tikzsetnextfilename{test1}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test1};\\n', '\\\\end{tikzpicture}\\n', '\\n', '% should be replaced in included file\\n', '\\\\input{figures/figure_included.tikz}\\n', '\\n', '% should not be be replaced - no preceding tikzsetnextfilename command\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test3};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\tikzsetnextfilename{test_no_match}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test4};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\end{document}\\n'], {'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False, 'to_delete': ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'], 'figures_to_copy_if_referenced': ['\\\\.png$', '\\\\.jpg$', '\\\\.jpeg$', '\\\\.pdf$'], 'output_folder': '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv'})", "loop_code": "1: def _remove_comments_and_commands_to_delete(content, parameters):\n2: \"\"\"Erases all LaTeX comments in the content, and writes it.\"\"\"\n3: content = [_remove_comments_inline(line) for line in content]\n4: content = _remove_environment(''.join(content), 'comment')\n5: content = _remove_iffalse_block(content)\n6: for environment in parameters.get('environments_to_delete', []):\n7: content = _remove_environment(content, environment)\n8: for command in parameters.get('commands_only_to_delete', []):\n9: content = _remove_command(content, command, True)\n10: for command in parameters['commands_to_delete']:\n11: content = _remove_command(content, command, False)\n12: return content\n13:\n14: _remove_comments_and_commands_to_delete(['\\\\begin{document}\\n', 'Text\\n', '% Whole line comment\\n', '\\n', 'Text% Inline comment\\n', '\\\\begin{comment}\\n', 'This is an environment comment.\\n', '\\\\end{comment}\\n', '\\n', 'This is a percent \\\\%.\\n', '% Whole line comment without newline\\n', '\\\\includegraphics{images/im1_included.png}\\n', '%\\\\includegraphics{images/im_not_included}\\n', '\\\\includegraphics{images/im3_included.png}\\n', '\\\\includegraphics{%\\n', ' images/im4_included.png%\\n', ' }\\n', '\\\\includegraphics[width=.5\\\\linewidth]{%\\n', ' images/im5_included.jpg}\\n', '%\\\\includegraphics{%\\n', '% images/im4_not_included.png\\n', '% }\\n', '%\\\\includegraphics[width=.5\\\\linewidth]{%\\n', '% images/im5_not_included.jpg}\\n', '\\n', '% test whatever the path satrting with dot works when include graphics\\n', '\\\\includegraphics{./images/im3_included.png}\\n', '\\n', 'This line should\\\\mytodo{Do this later} not be separated\\n', '\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\n', 'Please remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\n', 'from this one.\\n', '\\n', '\\\\begin{mynote}\\n', ' This is a custom environment that could be excluded.\\n', '\\\\end{mynote}\\n', '\\n', '\\\\newif\\\\ifvar\\n', '\\n', '\\\\ifvar\\n', '\\\\if false\\n', '\\\\if false\\n', '\\\\if 0\\n', '\\\\iffalse\\n', '\\\\ifvar\\n', 'Text\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\n', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\n', 'hello test \\\\red{hello\\n', 'test \\\\red{hello}}\\n', 'test\\n', '\\n', '% content after this line should not be cleaned if \\\\end{document} is in a comment\\n', '\\n', '\\\\input{figures/figure_included.tex}\\n', '% \\\\input{figures/figure_not_included.tex}\\n', '\\n', '% Test for tikzpicture feature\\n', '% should be replaced\\n', '\\\\tikzsetnextfilename{test1}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test1};\\n', '\\\\end{tikzpicture}\\n', '\\n', '% should be replaced in included file\\n', '\\\\input{figures/figure_included.tikz}\\n', '\\n', '% should not be be replaced - no preceding tikzsetnextfilename command\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test3};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\tikzsetnextfilename{test_no_match}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test4};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\end{document}\\n'], {'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False, 'to_delete': ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'], 'figures_to_copy_if_referenced': ['\\\\.png$', '\\\\.jpg$', '\\\\.jpeg$', '\\\\.pdf$'], 'output_folder': '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv'})", "question": "What is the value of 'command' in line 8 after executing '_remove_comments_and_commands_to_delete(['\\\\begin{document}\\n', 'Text\\n', '% Whole line comment\\n', '\\n', 'Text% Inline comment\\n', '\\\\begin{comment}\\n', 'This is an environment comment.\\n', '\\\\end{comment}\\n', '\\n', 'This is a percent \\\\%.\\n', '% Whole line comment without newline\\n', '\\\\includegraphics{images/im1_included.png}\\n', '%\\\\includegraphics{images/im_not_included}\\n', '\\\\includegraphics{images/im3_included.png}\\n', '\\\\includegraphics{%\\n', ' images/im4_included.png%\\n', ' }\\n', '\\\\includegraphics[width=.5\\\\linewidth]{%\\n', ' images/im5_included.jpg}\\n', '%\\\\includegraphics{%\\n', '% images/im4_not_included.png\\n', '% }\\n', '%\\\\includegraphics[width=.5\\\\linewidth]{%\\n', '% images/im5_not_included.jpg}\\n', '\\n', '% test whatever the path satrting with dot works when include graphics\\n', '\\\\includegraphics{./images/im3_included.png}\\n', '\\n', 'This line should\\\\mytodo{Do this later} not be separated\\n', '\\\\mytodo{This is a todo command with a nested \\\\textit{command}.\\n', 'Please remember that up to \\\\texttt{2 levels} of \\\\textit{nesting} are supported.}\\n', 'from this one.\\n', '\\n', '\\\\begin{mynote}\\n', ' This is a custom environment that could be excluded.\\n', '\\\\end{mynote}\\n', '\\n', '\\\\newif\\\\ifvar\\n', '\\n', '\\\\ifvar\\n', '\\\\if false\\n', '\\\\if false\\n', '\\\\if 0\\n', '\\\\iffalse\\n', '\\\\ifvar\\n', 'Text\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\\\fi\\n', '\\n', '\\\\newcommand{\\\\red}[1]{{\\\\color{red} #1}}\\n', 'hello test \\\\red{hello\\n', 'test \\\\red{hello}}\\n', 'test\\n', '\\n', '% content after this line should not be cleaned if \\\\end{document} is in a comment\\n', '\\n', '\\\\input{figures/figure_included.tex}\\n', '% \\\\input{figures/figure_not_included.tex}\\n', '\\n', '% Test for tikzpicture feature\\n', '% should be replaced\\n', '\\\\tikzsetnextfilename{test1}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test1};\\n', '\\\\end{tikzpicture}\\n', '\\n', '% should be replaced in included file\\n', '\\\\input{figures/figure_included.tikz}\\n', '\\n', '% should not be be replaced - no preceding tikzsetnextfilename command\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test3};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\tikzsetnextfilename{test_no_match}\\n', '\\\\begin{tikzpicture}\\n', ' \\\\node (test) at (0,0) {Test4};\\n', '\\\\end{tikzpicture}\\n', '\\n', '\\\\end{document}\\n'], {'input_folder': 'tex', 'images_allowlist': {'images/im2_included.jpg': 200, 'images/im3_included.png': 400}, 'resize_images': True, 'im_size': 100, 'compress_pdf': False, 'pdf_im_resolution': 500, 'commands_to_delete': ['mytodo'], 'commands_only_to_delete': ['red'], 'environments_to_delete': ['mynote'], 'use_external_tikz': 'ext_tikz', 'keep_bib': False, 'to_delete': ['\\\\.aux$', '\\\\.sh$', '\\\\.blg$', '\\\\.brf$', '\\\\.log$', '\\\\.out$', '\\\\.ps$', '\\\\.dvi$', '\\\\.synctex.gz$', '~$', '\\\\.backup$', '\\\\.gitignore$', '\\\\.DS_Store$', '\\\\.svg$', '^\\\\.idea', '\\\\.dpth$', '\\\\.md5$', '\\\\.dep$', '\\\\.auxlock$', '\\\\.fls$', '\\\\.fdb_latexmk$', '\\\\.bib$'], 'figures_to_copy_if_referenced': ['\\\\.png$', '\\\\.jpg$', '\\\\.jpeg$', '\\\\.pdf$'], 'output_folder': '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/google-research+arxiv-latex-cleaner/google-research+arxiv-latex-cleaner/tex_arXiv'})'?", "answer": "'red'", "variable_assignment": "command = 'red'", "loop_range": [6, 7], "post_loop_line": 8} {"idx": 10, "scratchpad_format": "def apply_changes(file_path: str, changes: List, confirm: bool = False):\n \"\"\"\n Pass changes as loaded json (list of dicts)\n \"\"\"\n with open(file_path) as f: # [STATE] f = <_io.TextIOWrapper name='/tmp/tmp6qrrn_j9' mode='r' encoding='UTF-8'> [/STATE]\n original_file_lines = f.readlines() # [STATE] original_file_lines = ['first line\\n', 'second line\\n', 'third line'] [/STATE]\n\n # Filter out explanation elements\n operation_changes = [change for change in changes if \"operation\" in change] # [STATE] operation_changes = [{'operation': 'Replace', 'line': 2, 'content': 'new second line'}] [/STATE]\n explanations = [ # [STATE] explanations = [] [/STATE]\n change[\"explanation\"] for change in changes if \"explanation\" in change\n ]\n\n # Sort the changes in reverse line order\n operation_changes.sort(key=lambda x: x[\"line\"], reverse=True)\n\n file_lines = original_file_lines.copy() # [STATE] file_lines = ['first line\\n', 'second line\\n', 'third line'] [/STATE]\n for change in operation_changes: # [STATE] change = {'operation': 'Replace', 'line': 2, 'content': 'new second line'} [/STATE]\n operation = change[\"operation\"] # [STATE] operation = 'Replace' [/STATE]\n line = change[\"line\"] # [STATE] line = 2 [/STATE]\n content = change[\"content\"] # [STATE] content = 'new second line' [/STATE]\n\n if operation == \"Replace\":\n file_lines[line - 1] = content + \"\\n\" # [STATE] file_lines = ['first line\\n', 'new second line\\n', 'third line'] [/STATE]\n elif operation == \"Delete\":\n del file_lines[line - 1]\n elif operation == \"InsertAfter\":\n file_lines.insert(line, content + \"\\n\")\n\n # Print explanations\n cprint(\"Explanations:\", \"blue\")\n for explanation in explanations:\n cprint(f\"- {explanation}\", \"blue\")\n\n # Display changes diff\n print(\"\\nChanges to be made:\")\n diff = difflib.unified_diff(original_file_lines, file_lines, lineterm=\"\") # [STATE] diff = [/STATE]\n for line in diff: # [STATE] line = '--- ' [/STATE] [STATE] line = '+++ ' [/STATE] [STATE] line = '@@ -1,3 +1,3 @@' [/STATE] [STATE] line = ' first line\\n' [/STATE] [STATE] line = '-second line\\n' [/STATE] [STATE] line = '+new second line\\n' [/STATE] [STATE] line = ' third line' [/STATE]\n if line.startswith(\"+\"):\n cprint(line, \"green\", end=\"\")\n elif line.startswith(\"-\"):\n cprint(line, \"red\", end=\"\")\n else:\n print(line, end=\"\")\n\n if confirm:\n # check if user wants to apply changes or exit\n confirmation = input(\"Do you want to apply these changes? (y/n): \")\n if confirmation.lower() != \"y\":\n print(\"Changes not applied\")\n sys.exit(0)\n\n with open(file_path, \"w\") as f: # [STATE] f = <_io.TextIOWrapper name='/tmp/tmp6qrrn_j9' mode='w' encoding='UTF-8'> [/STATE]\n f.writelines(file_lines)\n print(\"Changes applied.\")\n\napply_changes('/tmp/tmp6qrrn_j9', [{'operation': 'Replace', 'line': 2, 'content': 'new second line'}], False)", "loop_code": "1: def apply_changes(file_path: str, changes: List, confirm: bool = False):\n2: \"\"\"\n3: Pass changes as loaded json (list of dicts)\n4: \"\"\"\n5: with open(file_path) as f:\n6: original_file_lines = f.readlines()\n7:\n8: # Filter out explanation elements\n9: operation_changes = [change for change in changes if \"operation\" in change]\n10: explanations = [\n11: change[\"explanation\"] for change in changes if \"explanation\" in change\n12: ]\n13:\n14: # Sort the changes in reverse line order\n15: operation_changes.sort(key=lambda x: x[\"line\"], reverse=True)\n16:\n17: file_lines = original_file_lines.copy()\n18: for change in operation_changes:\n19: operation = change[\"operation\"]\n20: line = change[\"line\"]\n21: content = change[\"content\"]\n22:\n23: if operation == \"Replace\":\n24: file_lines[line - 1] = content + \"\\n\"\n25: elif operation == \"Delete\":\n26: del file_lines[line - 1]\n27: elif operation == \"InsertAfter\":\n28: file_lines.insert(line, content + \"\\n\")\n29:\n30: # Print explanations\n31: cprint(\"Explanations:\", \"blue\")\n32: for explanation in explanations:\n33: cprint(f\"- {explanation}\", \"blue\")\n34:\n35: # Display changes diff\n36: print(\"\\nChanges to be made:\")\n37: diff = difflib.unified_diff(original_file_lines, file_lines, lineterm=\"\")\n38: for line in diff:\n39: if line.startswith(\"+\"):\n40: cprint(line, \"green\", end=\"\")\n41: elif line.startswith(\"-\"):\n42: cprint(line, \"red\", end=\"\")\n43: else:\n44: print(line, end=\"\")\n45:\n46: if confirm:\n47: # check if user wants to apply changes or exit\n48: confirmation = input(\"Do you want to apply these changes? (y/n): \")\n49: if confirmation.lower() != \"y\":\n50: print(\"Changes not applied\")\n51: sys.exit(0)\n52:\n53: with open(file_path, \"w\") as f:\n54: f.writelines(file_lines)\n55: print(\"Changes applied.\")\n56:\n57: apply_changes('/tmp/tmp6qrrn_j9', [{'operation': 'Replace', 'line': 2, 'content': 'new second line'}], False)", "question": "What is the value of 'f' in line 53 after executing 'apply_changes('/tmp/tmp6qrrn_j9', [{'operation': 'Replace', 'line': 2, 'content': 'new second line'}], False)'?", "answer": "<_io.TextIOWrapper name='/tmp/tmp6qrrn_j9' mode='w' encoding='UTF-8'>", "variable_assignment": "f = <_io.TextIOWrapper name='/tmp/tmp6qrrn_j9' mode='w' encoding='UTF-8'>", "loop_range": [38, 44], "post_loop_line": 53} {"idx": 11, "scratchpad_format": "def parse_layout(layout_str):\n \"\"\"Parse a layout string\n\n Return a dict\n {'walls': list_of_wall_coordinates,\n 'food' : list_of_food_coordinates,\n 'bot' : list_of_4_bot_coordinate}\n\n A layout string is composed of wall characters '#', food characters '.', and\n bot characters '0', '1', '2', and '3'.\n\n Valid layouts must be enclosed by walls and be of rectangular shape. Example:\n\n ########\n #0 . #\n #2 1#\n # . 3#\n ########\n\n\n If items are overlapping, several layout strings can be concateneted:\n ########\n #0 . #\n # 1#\n # . 3#\n ########\n ########\n #2 . #\n # 1#\n # . 3#\n ########\n\n In this case, bot '0' and bot '2' are on top of each other at position (1,1)\n \"\"\"\n layout_list = [] # [STATE] layout_list = [] [/STATE]\n start = False # [STATE] start = False [/STATE]\n for i, line in enumerate(layout_str.splitlines()): # [STATE] i = 0 [/STATE] [STATE] line = '' [/STATE] [STATE] i = 1 [/STATE] [STATE] line = ' ##################' [/STATE] [STATE] i = 2 [/STATE] [STATE] line = ' #. ... .##. 3#' [/STATE] [STATE] i = 3 [/STATE] [STATE] line = ' # # # . .### #1#' [/STATE] [STATE] i = 4 [/STATE] [STATE] line = ' # # ##. . #' [/STATE] [STATE] i = 5 [/STATE] [STATE] line = ' # . .## # #' [/STATE] [STATE] i = 6 [/STATE] [STATE] line = ' #0# ###. . # # #' [/STATE] [STATE] i = 7 [/STATE] [STATE] line = ' #2 .##. ... .#' [/STATE] [STATE] i = 8 [/STATE] [STATE] line = ' ################## ' [/STATE]\n row = line.strip() # [STATE] row = '' [/STATE] [STATE] row = '##################' [/STATE] [STATE] row = '#. ... .##. 3#' [/STATE] [STATE] row = '# # # . .### #1#' [/STATE] [STATE] row = '# # ##. . #' [/STATE] [STATE] row = '# . .## # #' [/STATE] [STATE] row = '#0# ###. . # # #' [/STATE] [STATE] row = '#2 .##. ... .#' [/STATE]\n if not row:\n # ignore emptylines\n continue\n if not start:\n # start a new layout\n # check that row is a valid opening string\n if row.count('#') != len(row):\n raise ValueError(f\"Layout does not start with a row of walls (line: {i})!\")\n current_layout = [row] # [STATE] current_layout = ['##################'] [/STATE]\n start = True # [STATE] start = True [/STATE]\n continue\n # we are in the middle of a layout, just append to the current\n # layout unless we detect the closing string\n current_layout.append(row) # [STATE] current_layout = ['##################', '#. ... .##. 3#'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #', '#2 .##. ... .#'] [/STATE] [STATE] current_layout = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #', '#2 .##. ... .#', '##################'] [/STATE]\n if row.count('#') == len(row):\n # this is a closing string\n # append the layout to tha layout list\n layout_list.append('\\n'.join(current_layout)) # [STATE] layout_list = ['##################\\n#. ... .##. 3#\\n# # # . .### #1#\\n# # ##. . #\\n# . .## # #\\n#0# ###. . # # #\\n#2 .##. ... .#\\n##################'] [/STATE]\n start = False # [STATE] start = False [/STATE]\n\n if start:\n # the last layout has not been closed, complain here!\n raise ValueError(f\"Layout does not end with a row of walls (line: {i})!\")\n\n # initialize walls, food and bots from the first layout\n out = parse_single_layout(layout_list.pop(0)) # [STATE] out = {'walls': [(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 0), (1, 7), (2, 0), (2, 2), (2, 3), (2, 5), (2, 7), (3, 0), (3, 7), (4, 0), (4, 2), (4, 3), (4, 5), (4, 7), (5, 0), (5, 3), (5, 5), (5, 7), (6, 0), (6, 5), (6, 7), (7, 0), (7, 7), (8, 0), (8, 1), (8, 6), (8, 7), (9, 0), (9, 1), (9, 6), (9, 7), (10, 0), (10, 7), (11, 0), (11, 2), (11, 7), (12, 0), (12, 2), (12, 4), (12, 7), (13, 0), (13, 2), (13, 4), (13, 5), (13, 7), (14, 0), (14, 7), (15, 0), (15, 2), (15, 4), (15, 5), (15, 7), (16, 0), (16, 7), (17, 0), (17, 1), (17, 2), (17, 3), (17, 4), (17, 5), (17, 6), (17, 7)], 'food': [(1, 1), (3, 1), (4, 1), (5, 1), (6, 3), (7, 1), (7, 2), (7, 4), (7, 5), (7, 6), (10, 1), (10, 2), (10, 3), (10, 5), (10, 6), (11, 4), (12, 6), (13, 6), (14, 6), (16, 6)], 'bots': [(1, 5), (16, 2), (1, 6), (16, 1)]} [/STATE] # [STATE] layout_list = [] [/STATE]\n for layout in layout_list:\n items = parse_layout(layout)\n # walls should always be the same\n if items['walls'] != out['walls']:\n raise ValueError('Walls are not equal in all layouts!')\n # add the food, removing duplicates\n out['food'] = list(set(out['food'] + items['food']))\n # add the bots\n for bot_idx, bot_pos in enumerate(items['bots']):\n if bot_pos:\n # this bot position is not None, overwrite whatever we had before\n out['bots'][bot_idx] = bot_pos\n\n return out\n\nparse_layout('\\n ##################\\n #. ... .##. 3#\\n # # # . .### #1#\\n # # ##. . #\\n # . .## # #\\n #0# ###. . # # #\\n #2 .##. ... .#\\n ################## ')", "loop_code": "1: def parse_layout(layout_str):\n2: \"\"\"Parse a layout string\n3:\n4: Return a dict\n5: {'walls': list_of_wall_coordinates,\n6: 'food' : list_of_food_coordinates,\n7: 'bot' : list_of_4_bot_coordinate}\n8:\n9: A layout string is composed of wall characters '#', food characters '.', and\n10: bot characters '0', '1', '2', and '3'.\n11:\n12: Valid layouts must be enclosed by walls and be of rectangular shape. Example:\n13:\n14: ########\n15: #0 . #\n16: #2 1#\n17: # . 3#\n18: ########\n19:\n20:\n21: If items are overlapping, several layout strings can be concateneted:\n22: ########\n23: #0 . #\n24: # 1#\n25: # . 3#\n26: ########\n27: ########\n28: #2 . #\n29: # 1#\n30: # . 3#\n31: ########\n32:\n33: In this case, bot '0' and bot '2' are on top of each other at position (1,1)\n34: \"\"\"\n35: layout_list = []\n36: start = False\n37: for i, line in enumerate(layout_str.splitlines()):\n38: row = line.strip()\n39: if not row:\n40: # ignore emptylines\n41: continue\n42: if not start:\n43: # start a new layout\n44: # check that row is a valid opening string\n45: if row.count('#') != len(row):\n46: raise ValueError(f\"Layout does not start with a row of walls (line: {i})!\")\n47: current_layout = [row]\n48: start = True\n49: continue\n50: # we are in the middle of a layout, just append to the current\n51: # layout unless we detect the closing string\n52: current_layout.append(row)\n53: if row.count('#') == len(row):\n54: # this is a closing string\n55: # append the layout to tha layout list\n56: layout_list.append('\\n'.join(current_layout))\n57: start = False\n58:\n59: if start:\n60: # the last layout has not been closed, complain here!\n61: raise ValueError(f\"Layout does not end with a row of walls (line: {i})!\")\n62:\n63: # initialize walls, food and bots from the first layout\n64: out = parse_single_layout(layout_list.pop(0))\n65: for layout in layout_list:\n66: items = parse_layout(layout)\n67: # walls should always be the same\n68: if items['walls'] != out['walls']:\n69: raise ValueError('Walls are not equal in all layouts!')\n70: # add the food, removing duplicates\n71: out['food'] = list(set(out['food'] + items['food']))\n72: # add the bots\n73: for bot_idx, bot_pos in enumerate(items['bots']):\n74: if bot_pos:\n75: # this bot position is not None, overwrite whatever we had before\n76: out['bots'][bot_idx] = bot_pos\n77:\n78: return out\n79:\n80: parse_layout('\\n ##################\\n #. ... .##. 3#\\n # # # . .### #1#\\n # # ##. . #\\n # . .## # #\\n #0# ###. . # # #\\n #2 .##. ... .#\\n ################## ')", "question": "What is the value of 'out' in line 64 after executing 'parse_layout('\\n ##################\\n #. ... .##. 3#\\n # # # . .### #1#\\n # # ##. . #\\n # . .## # #\\n #0# ###. . # # #\\n #2 .##. ... .#\\n ################## ')'?", "answer": "{'walls': [(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 0), (1, 7), (2, 0), (2, 2), (2, 3), (2, 5), (2, 7), (3, 0), (3, 7), (4, 0), (4, 2), (4, 3), (4, 5), (4, 7), (5, 0), (5, 3), (5, 5), (5, 7), (6, 0), (6, 5), (6, 7), (7, 0), (7, 7), (8, 0), (8, 1), (8, 6), (8, 7), (9, 0), (9, 1), (9, 6), (9, 7), (10, 0), (10, 7), (11, 0), (11, 2), (11, 7), (12, 0), (12, 2), (12, 4), (12, 7), (13, 0), (13, 2), (13, 4), (13, 5), (13, 7), (14, 0), (14, 7), (15, 0), (15, 2), (15, 4), (15, 5), (15, 7), (16, 0), (16, 7), (17, 0), (17, 1), (17, 2), (17, 3), (17, 4), (17, 5), (17, 6), (17, 7)], 'food': [(1, 1), (3, 1), (4, 1), (5, 1), (6, 3), (7, 1), (7, 2), (7, 4), (7, 5), (7, 6), (10, 1), (10, 2), (10, 3), (10, 5), (10, 6), (11, 4), (12, 6), (13, 6), (14, 6), (16, 6)], 'bots': [(1, 5), (16, 2), (1, 6), (16, 1)]}", "variable_assignment": "out = {'walls': [(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 0), (1, 7), (2, 0), (2, 2), (2, 3), (2, 5), (2, 7), (3, 0), (3, 7), (4, 0), (4, 2), (4, 3), (4, 5), (4, 7), (5, 0), (5, 3), (5, 5), (5, 7), (6, 0), (6, 5), (6, 7), (7, 0), (7, 7), (8, 0), (8, 1), (8, 6), (8, 7), (9, 0), (9, 1), (9, 6), (9, 7), (10, 0), (10, 7), (11, 0), (11, 2), (11, 7), (12, 0), (12, 2), (12, 4), (12, 7), (13, 0), (13, 2), (13, 4), (13, 5), (13, 7), (14, 0), (14, 7), (15, 0), (15, 2), (15, 4), (15, 5), (15, 7), (16, 0), (16, 7), (17, 0), (17, 1), (17, 2), (17, 3), (17, 4), (17, 5), (17, 6), (17, 7)], 'food': [(1, 1), (3, 1), (4, 1), (5, 1), (6, 3), (7, 1), (7, 2), (7, 4), (7, 5), (7, 6), (10, 1), (10, 2), (10, 3), (10, 5), (10, 6), (11, 4), (12, 6), (13, 6), (14, 6), (16, 6)], 'bots': [(1, 5), (16, 2), (1, 6), (16, 1)]}", "loop_range": [37, 57], "post_loop_line": 64} {"idx": 12, "scratchpad_format": "def parse_single_layout(layout_str):\n \"\"\"Parse a single layout from a string\n\n See parse_layout for details about valid layout strings.\n \"\"\"\n # width of the layout (x-axis)\n width = None # [STATE] width = None [/STATE]\n # list of layout rows\n rows = [] # [STATE] rows = [] [/STATE]\n start = False # [STATE] start = False [/STATE]\n for i, line in enumerate(layout_str.splitlines()): # [STATE] i = 0 [/STATE] [STATE] line = '##################' [/STATE] [STATE] i = 1 [/STATE] [STATE] line = '#. ... .##. 3#' [/STATE] [STATE] i = 2 [/STATE] [STATE] line = '# # # . .### #1#' [/STATE] [STATE] i = 3 [/STATE] [STATE] line = '# # ##. . #' [/STATE] [STATE] i = 4 [/STATE] [STATE] line = '# . .## # #' [/STATE] [STATE] i = 5 [/STATE] [STATE] line = '#0# ###. . # # #' [/STATE] [STATE] i = 6 [/STATE] [STATE] line = '#2 .##. ... .#' [/STATE] [STATE] i = 7 [/STATE]\n row = line.strip() # [STATE] row = '##################' [/STATE] [STATE] row = '#. ... .##. 3#' [/STATE] [STATE] row = '# # # . .### #1#' [/STATE] [STATE] row = '# # ##. . #' [/STATE] [STATE] row = '# . .## # #' [/STATE] [STATE] row = '#0# ###. . # # #' [/STATE] [STATE] row = '#2 .##. ... .#' [/STATE]\n if not row:\n # always ignore empty lines\n continue\n # a layout is always started by a full row of walls\n if not start:\n if row.count('#') != len(row):\n raise ValueError(f\"Layout must be enclosed by walls (line: {i})!\")\n else:\n # start the layout parsing\n start = True # [STATE] start = True [/STATE]\n # set width of layout\n width = len(row) # [STATE] width = 18 [/STATE]\n # check that width is even\n if width % 2:\n raise ValueError(f\"Layout width must be even (found {width})!\")\n rows.append(row) # [STATE] rows = ['##################'] [/STATE]\n continue\n # Here we are within the layout\n # every row must have the same length\n if len(row) != width:\n raise ValueError(f\"Layout rows have differing widths (line: {i})!\")\n # rows are always enclosed by walls\n if row[0] != '#' or row[-1] != '#':\n raise ValueError(f\"Layout must be enclosed by walls (line:{i})!\")\n # append current row to the list of rows\n rows.append(row) # [STATE] rows = ['##################', '#. ... .##. 3#'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #', '#2 .##. ... .#'] [/STATE] [STATE] rows = ['##################', '#. ... .##. 3#', '# # # . .### #1#', '# # ##. . #', '# . .## # #', '#0# ###. . # # #', '#2 .##. ... .#', '##################'] [/STATE]\n # detect closing row and ignore whatever follows\n if row.count('#') == len(row):\n start = False # [STATE] start = False [/STATE]\n break\n\n if start:\n # layout has not been closed!\n raise ValueError(f\"Layout must be enclosed by walls (line:{i})!\")\n\n # height of the layout (y-axis)\n height = len(rows) # [STATE] height = 8 [/STATE]\n walls = [] # [STATE] walls = [] [/STATE]\n food = [] # [STATE] food = [] [/STATE]\n # bot positions (we assume 4 bots)\n bots = [None]*4 # [STATE] bots = [None, None, None, None] [/STATE]\n\n # iterate through the grid of characters\n for y, row in enumerate(rows): # [STATE] y = 0 [/STATE] [STATE] row = '#. ... .##. 3#' [/STATE] [STATE] y = 1 [/STATE] [STATE] row = '# # # . .### #1#' [/STATE] [STATE] y = 2 [/STATE] [STATE] row = '# # ##. . #' [/STATE] [STATE] y = 3 [/STATE] [STATE] row = '# . .## # #' [/STATE] [STATE] y = 4 [/STATE] [STATE] row = '#0# ###. . # # #' [/STATE] [STATE] y = 5 [/STATE] [STATE] row = '#2 .##. ... .#' [/STATE] [STATE] y = 6 [/STATE] [STATE] row = '##################' [/STATE] [STATE] y = 7 [/STATE]\n for x, char in enumerate(row): # [STATE] x = 0 [/STATE] [STATE] char = '#' [/STATE] [STATE] x = 1 [/STATE] [STATE] x = 2 [/STATE] [STATE] x = 3 [/STATE] [STATE] x = 4 [/STATE] [STATE] x = 5 [/STATE] [STATE] x = 6 [/STATE] [STATE] x = 7 [/STATE] [STATE] x = 8 [/STATE] [STATE] x = 9 [/STATE] [STATE] x = 10 [/STATE] [STATE] x = 11 [/STATE] [STATE] x = 12 [/STATE] [STATE] x = 13 [/STATE] [STATE] x = 14 [/STATE] [STATE] x = 15 [/STATE] [STATE] x = 16 [/STATE] [STATE] x = 17 [/STATE] [STATE] char = '.' [/STATE] [STATE] char = ' ' [/STATE]\n coord = (x, y) # [STATE] coord = (0, 0) [/STATE] [STATE] coord = (1, 0) [/STATE] [STATE] coord = (2, 0) [/STATE] [STATE] coord = (3, 0) [/STATE] [STATE] coord = (4, 0) [/STATE] [STATE] coord = (5, 0) [/STATE] [STATE] coord = (6, 0) [/STATE] [STATE] coord = (7, 0) [/STATE] [STATE] coord = (8, 0) [/STATE] [STATE] coord = (9, 0) [/STATE] [STATE] coord = (10, 0) [/STATE] [STATE] coord = (11, 0) [/STATE] [STATE] coord = (12, 0) [/STATE] [STATE] coord = (13, 0) [/STATE] [STATE] coord = (14, 0) [/STATE] [STATE] coord = (15, 0) [/STATE] [STATE] coord = (16, 0) [/STATE] [STATE] coord = (17, 0) [/STATE] [STATE] coord = (0, 1) [/STATE] [STATE] coord = (1, 1) [/STATE] [STATE] coord = (2, 1) [/STATE]\n # assign the char to the corresponding list\n if char == '#':\n # wall\n walls.append(coord) # [STATE] walls = [(0, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0), (17, 0)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0), (17, 0), (0, 1)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0), (17, 0), (0, 1), (8, 1)] [/STATE] [STATE] walls = [(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (10, 0), (11, 0), (12, 0), (13, 0), (14, 0), (15, 0), (16, 0), (17, 0), (0, 1), (8, 1), (9, 1)] [/STATE]\n elif char == '.':\n # food\n food.append(coord) # [STATE] food = [(1, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6), (10, 6)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6), (10, 6), (12, 6)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6), (10, 6), (12, 6), (13, 6)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6), (10, 6), (12, 6), (13, 6), (14, 6)] [/STATE] [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (7, 1), (10, 1), (7, 2), (10, 2), (6, 3), (10, 3), (7, 4), (11, 4), (7, 5), (10, 5), (7, 6), (10, 6), (12, 6), (13, 6), (14, 6), (16, 6)] [/STATE]\n elif char == ' ':\n # empty\n continue\n else:\n # bot\n try:\n # we expect an 0<=index<=3\n bot_idx = int(char) # [STATE] bot_idx = 3 [/STATE] [STATE] bot_idx = 1 [/STATE] [STATE] bot_idx = 0 [/STATE] [STATE] bot_idx = 2 [/STATE]\n if bot_idx >= len(bots):\n # reuse the except below\n raise ValueError\n except ValueError:\n raise ValueError(f\"Unknown character {char} in maze!\")\n bots[bot_idx] = coord # [STATE] bots = [None, None, None, (16, 1)] [/STATE] [STATE] bots = [None, (16, 2), None, (16, 1)] [/STATE] [STATE] bots = [(1, 5), (16, 2), None, (16, 1)] [/STATE] [STATE] bots = [(1, 5), (16, 2), (1, 6), (16, 1)] [/STATE]\n walls.sort() # [STATE] walls = [(0, 0), (0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (0, 7), (1, 0), (1, 7), (2, 0), (2, 2), (2, 3), (2, 5), (2, 7), (3, 0), (3, 7), (4, 0), (4, 2), (4, 3), (4, 5), (4, 7), (5, 0), (5, 3), (5, 5), (5, 7), (6, 0), (6, 5), (6, 7), (7, 0), (7, 7), (8, 0), (8, 1), (8, 6), (8, 7), (9, 0), (9, 1), (9, 6), (9, 7), (10, 0), (10, 7), (11, 0), (11, 2), (11, 7), (12, 0), (12, 2), (12, 4), (12, 7), (13, 0), (13, 2), (13, 4), (13, 5), (13, 7), (14, 0), (14, 7), (15, 0), (15, 2), (15, 4), (15, 5), (15, 7), (16, 0), (16, 7), (17, 0), (17, 1), (17, 2), (17, 3), (17, 4), (17, 5), (17, 6), (17, 7)] [/STATE]\n food.sort() # [STATE] food = [(1, 1), (3, 1), (4, 1), (5, 1), (6, 3), (7, 1), (7, 2), (7, 4), (7, 5), (7, 6), (10, 1), (10, 2), (10, 3), (10, 5), (10, 6), (11, 4), (12, 6), (13, 6), (14, 6), (16, 6)] [/STATE]\n return {'walls':walls, 'food':food, 'bots':bots}\n\nparse_single_layout('##################\\n#. ... .##. 3#\\n# # # . .### #1#\\n# # ##. . #\\n# . .## # #\\n#0# ###. . # # #\\n#2 .##. ... .#\\n##################')", "loop_code": "1: def parse_single_layout(layout_str):\n2: \"\"\"Parse a single layout from a string\n3:\n4: See parse_layout for details about valid layout strings.\n5: \"\"\"\n6: # width of the layout (x-axis)\n7: width = None\n8: # list of layout rows\n9: rows = []\n10: start = False\n11: for i, line in enumerate(layout_str.splitlines()):\n12: row = line.strip()\n13: if not row:\n14: # always ignore empty lines\n15: continue\n16: # a layout is always started by a full row of walls\n17: if not start:\n18: if row.count('#') != len(row):\n19: raise ValueError(f\"Layout must be enclosed by walls (line: {i})!\")\n20: else:\n21: # start the layout parsing\n22: start = True\n23: # set width of layout\n24: width = len(row)\n25: # check that width is even\n26: if width % 2:\n27: raise ValueError(f\"Layout width must be even (found {width})!\")\n28: rows.append(row)\n29: continue\n30: # Here we are within the layout\n31: # every row must have the same length\n32: if len(row) != width:\n33: raise ValueError(f\"Layout rows have differing widths (line: {i})!\")\n34: # rows are always enclosed by walls\n35: if row[0] != '#' or row[-1] != '#':\n36: raise ValueError(f\"Layout must be enclosed by walls (line:{i})!\")\n37: # append current row to the list of rows\n38: rows.append(row)\n39: # detect closing row and ignore whatever follows\n40: if row.count('#') == len(row):\n41: start = False\n42: break\n43:\n44: if start:\n45: # layout has not been closed!\n46: raise ValueError(f\"Layout must be enclosed by walls (line:{i})!\")\n47:\n48: # height of the layout (y-axis)\n49: height = len(rows)\n50: walls = []\n51: food = []\n52: # bot positions (we assume 4 bots)\n53: bots = [None]*4\n54:\n55: # iterate through the grid of characters\n56: for y, row in enumerate(rows):\n57: for x, char in enumerate(row):\n58: coord = (x, y)\n59: # assign the char to the corresponding list\n60: if char == '#':\n61: # wall\n62: walls.append(coord)\n63: elif char == '.':\n64: # food\n65: food.append(coord)\n66: elif char == ' ':\n67: # empty\n68: continue\n69: else:\n70: # bot\n71: try:\n72: # we expect an 0<=index<=3\n73: bot_idx = int(char)\n74: if bot_idx >= len(bots):\n75: # reuse the except below\n76: raise ValueError\n77: except ValueError:\n78: raise ValueError(f\"Unknown character {char} in maze!\")\n79: bots[bot_idx] = coord\n80: walls.sort()\n81: food.sort()\n82: return {'walls':walls, 'food':food, 'bots':bots}\n83:\n84: parse_single_layout('##################\\n#. ... .##. 3#\\n# # # . .### #1#\\n# # ##. . #\\n# . .## # #\\n#0# ###. . # # #\\n#2 .##. ... .#\\n##################')", "question": "What is the value of 'height' in line 49 after executing 'parse_single_layout('##################\\n#. ... .##. 3#\\n# # # . .### #1#\\n# # ##. . #\\n# . .## # #\\n#0# ###. . # # #\\n#2 .##. ... .#\\n##################')'?", "answer": "8", "variable_assignment": "height = 8", "loop_range": [11, 42], "post_loop_line": 49} {"idx": 13, "scratchpad_format": "def initial_positions(walls):\n \"\"\"Calculate initial positions.\n\n Given the list of walls, returns the free positions that are closest to the\n bottom left and top right corner. The algorithm starts searching from\n (1, height-2) and (width-2, 1) respectively and uses the Manhattan distance\n for judging what is closest. On equal distances, a smaller distance in the\n x value is preferred.\n \"\"\"\n width = max(walls)[0] + 1 # [STATE] width = 8 [/STATE]\n height = max(walls)[1] + 1 # [STATE] height = 4 [/STATE]\n\n left_start = (1, height - 2) # [STATE] left_start = (1, 2) [/STATE]\n left = [] # [STATE] left = [] [/STATE]\n right_start = (width - 2, 1) # [STATE] right_start = (6, 1) [/STATE]\n right = [] # [STATE] right = [] [/STATE]\n\n dist = 0 # [STATE] dist = 0 [/STATE]\n while len(left) < 2:\n # iterate through all possible x distances (inclusive)\n for x_dist in range(dist + 1): # [STATE] x_dist = 0 [/STATE]\n y_dist = dist - x_dist # [STATE] y_dist = 0 [/STATE] [STATE] y_dist = 1 [/STATE]\n pos = (left_start[0] + x_dist, left_start[1] - y_dist) # [STATE] pos = (1, 2) [/STATE] [STATE] pos = (1, 1) [/STATE]\n # if both coordinates are out of bounds, we stop\n if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):\n raise ValueError(\"Not enough free initial positions.\")\n # if one coordinate is out of bounds, we just continue\n if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):\n continue\n # check if the new value is free\n if pos not in walls:\n left.append(pos) # [STATE] left = [(1, 2)] [/STATE] [STATE] left = [(1, 2), (1, 1)] [/STATE]\n\n if len(left) == 2:\n break\n\n dist += 1 # [STATE] dist = 1 [/STATE] [STATE] dist = 2 [/STATE]\n\n dist = 0 # [STATE] dist = 0 [/STATE]\n while len(right) < 2:\n # iterate through all possible x distances (inclusive)\n for x_dist in range(dist + 1):\n y_dist = dist - x_dist # [STATE] y_dist = 0 [/STATE] [STATE] y_dist = 1 [/STATE]\n pos = (right_start[0] - x_dist, right_start[1] + y_dist) # [STATE] pos = (6, 1) [/STATE] [STATE] pos = (6, 2) [/STATE]\n # if both coordinates are out of bounds, we stop\n if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):\n raise ValueError(\"Not enough free initial positions.\")\n # if one coordinate is out of bounds, we just continue\n if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):\n continue\n # check if the new value is free\n if pos not in walls:\n right.append(pos) # [STATE] right = [(6, 1)] [/STATE] [STATE] right = [(6, 1), (6, 2)] [/STATE]\n\n if len(right) == 2:\n break\n\n dist += 1 # [STATE] dist = 1 [/STATE] [STATE] dist = 2 [/STATE]\n\n # lower indices start further away\n left.reverse() # [STATE] left = [(1, 1), (1, 2)] [/STATE]\n right.reverse() # [STATE] right = [(6, 2), (6, 1)] [/STATE]\n return [left[0], right[0], left[1], right[1]]\n\ninitial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])", "loop_code": "1: def initial_positions(walls):\n2: \"\"\"Calculate initial positions.\n3:\n4: Given the list of walls, returns the free positions that are closest to the\n5: bottom left and top right corner. The algorithm starts searching from\n6: (1, height-2) and (width-2, 1) respectively and uses the Manhattan distance\n7: for judging what is closest. On equal distances, a smaller distance in the\n8: x value is preferred.\n9: \"\"\"\n10: width = max(walls)[0] + 1\n11: height = max(walls)[1] + 1\n12:\n13: left_start = (1, height - 2)\n14: left = []\n15: right_start = (width - 2, 1)\n16: right = []\n17:\n18: dist = 0\n19: while len(left) < 2:\n20: # iterate through all possible x distances (inclusive)\n21: for x_dist in range(dist + 1):\n22: y_dist = dist - x_dist\n23: pos = (left_start[0] + x_dist, left_start[1] - y_dist)\n24: # if both coordinates are out of bounds, we stop\n25: if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):\n26: raise ValueError(\"Not enough free initial positions.\")\n27: # if one coordinate is out of bounds, we just continue\n28: if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):\n29: continue\n30: # check if the new value is free\n31: if pos not in walls:\n32: left.append(pos)\n33:\n34: if len(left) == 2:\n35: break\n36:\n37: dist += 1\n38:\n39: dist = 0\n40: while len(right) < 2:\n41: # iterate through all possible x distances (inclusive)\n42: for x_dist in range(dist + 1):\n43: y_dist = dist - x_dist\n44: pos = (right_start[0] - x_dist, right_start[1] + y_dist)\n45: # if both coordinates are out of bounds, we stop\n46: if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):\n47: raise ValueError(\"Not enough free initial positions.\")\n48: # if one coordinate is out of bounds, we just continue\n49: if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):\n50: continue\n51: # check if the new value is free\n52: if pos not in walls:\n53: right.append(pos)\n54:\n55: if len(right) == 2:\n56: break\n57:\n58: dist += 1\n59:\n60: # lower indices start further away\n61: left.reverse()\n62: right.reverse()\n63: return [left[0], right[0], left[1], right[1]]\n64:\n65: initial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])", "question": "What is the value of 'left' in line 61 after executing 'initial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])'?", "answer": "[(1, 1), (1, 2)]", "variable_assignment": "left = [(1, 1), (1, 2)]", "loop_range": [40, 58], "post_loop_line": 61} {"idx": 14, "scratchpad_format": "def process_fenced_block(lines, start_line_num):\n for line_num in range(start_line_num, len(lines)): # [STATE] line_num = 4 [/STATE] [STATE] line_num = 5 [/STATE] [STATE] line_num = 6 [/STATE] [STATE] line_num = 7 [/STATE] [STATE] line_num = 8 [/STATE] [STATE] line_num = 9 [/STATE]\n line = lines[line_num] # [STATE] line = '--- /dev/null\\n' [/STATE] [STATE] line = '+++ file.txt\\n' [/STATE] [STATE] line = '@@ ... @@\\n' [/STATE] [STATE] line = '-Original\\n' [/STATE] [STATE] line = '+Modified\\n' [/STATE] [STATE] line = '```\\n' [/STATE]\n if line.startswith(\"```\"):\n break\n\n block = lines[start_line_num:line_num] # [STATE] block = ['--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n'] [/STATE]\n block.append(\"@@ @@\") # [STATE] block = ['--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n', '@@ @@'] [/STATE]\n\n if block[0].startswith(\"--- \") and block[1].startswith(\"+++ \"):\n # Extract the file path, considering that it might contain spaces\n fname = block[1][4:].strip() # [STATE] fname = 'file.txt' [/STATE]\n block = block[2:] # [STATE] block = ['@@ ... @@\\n', '-Original\\n', '+Modified\\n', '@@ @@'] [/STATE]\n else:\n fname = None\n\n edits = [] # [STATE] edits = [] [/STATE]\n\n keeper = False # [STATE] keeper = False [/STATE]\n hunk = [] # [STATE] hunk = [] [/STATE]\n op = \" \" # [STATE] op = ' ' [/STATE]\n for line in block: # [STATE] line = '@@ ... @@\\n' [/STATE] [STATE] line = '-Original\\n' [/STATE] [STATE] line = '+Modified\\n' [/STATE] [STATE] line = '@@ @@' [/STATE]\n hunk.append(line) # [STATE] hunk = ['@@ ... @@\\n'] [/STATE] [STATE] hunk = ['-Original\\n'] [/STATE] [STATE] hunk = ['-Original\\n', '+Modified\\n'] [/STATE] [STATE] hunk = ['-Original\\n', '+Modified\\n', '@@ @@'] [/STATE]\n if len(line) < 2:\n continue\n\n if line.startswith(\"+++ \") and hunk[-2].startswith(\"--- \"):\n if hunk[-3] == \"\\n\":\n hunk = hunk[:-3]\n else:\n hunk = hunk[:-2]\n\n edits.append((fname, hunk))\n hunk = []\n keeper = False\n\n fname = line[4:].strip()\n continue\n\n op = line[0] # [STATE] op = '@' [/STATE] [STATE] op = '-' [/STATE] [STATE] op = '+' [/STATE]\n if op in \"-+\":\n keeper = True # [STATE] keeper = True [/STATE]\n continue\n if op != \"@\":\n continue\n if not keeper:\n hunk = [] # [STATE] hunk = [] [/STATE]\n continue\n\n hunk = hunk[:-1] # [STATE] hunk = ['-Original\\n', '+Modified\\n'] [/STATE]\n edits.append((fname, hunk)) # [STATE] edits = [('file.txt', ['-Original\\n', '+Modified\\n'])] [/STATE]\n hunk = [] # [STATE] hunk = [] [/STATE]\n keeper = False # [STATE] keeper = False [/STATE]\n\n return line_num + 1, edits\n\nprocess_fenced_block(['\\n', 'Some text...\\n', '\\n', '```diff\\n', '--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n', '```\\n'], 4)", "loop_code": "1: def process_fenced_block(lines, start_line_num):\n2: for line_num in range(start_line_num, len(lines)):\n3: line = lines[line_num]\n4: if line.startswith(\"```\"):\n5: break\n6:\n7: block = lines[start_line_num:line_num]\n8: block.append(\"@@ @@\")\n9:\n10: if block[0].startswith(\"--- \") and block[1].startswith(\"+++ \"):\n11: # Extract the file path, considering that it might contain spaces\n12: fname = block[1][4:].strip()\n13: block = block[2:]\n14: else:\n15: fname = None\n16:\n17: edits = []\n18:\n19: keeper = False\n20: hunk = []\n21: op = \" \"\n22: for line in block:\n23: hunk.append(line)\n24: if len(line) < 2:\n25: continue\n26:\n27: if line.startswith(\"+++ \") and hunk[-2].startswith(\"--- \"):\n28: if hunk[-3] == \"\\n\":\n29: hunk = hunk[:-3]\n30: else:\n31: hunk = hunk[:-2]\n32:\n33: edits.append((fname, hunk))\n34: hunk = []\n35: keeper = False\n36:\n37: fname = line[4:].strip()\n38: continue\n39:\n40: op = line[0]\n41: if op in \"-+\":\n42: keeper = True\n43: continue\n44: if op != \"@\":\n45: continue\n46: if not keeper:\n47: hunk = []\n48: continue\n49:\n50: hunk = hunk[:-1]\n51: edits.append((fname, hunk))\n52: hunk = []\n53: keeper = False\n54:\n55: return line_num + 1, edits\n56:\n57: process_fenced_block(['\\n', 'Some text...\\n', '\\n', '```diff\\n', '--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n', '```\\n'], 4)", "question": "What is the value of 'block' in line 7 after executing 'process_fenced_block(['\\n', 'Some text...\\n', '\\n', '```diff\\n', '--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n', '```\\n'], 4)'?", "answer": "['--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n']", "variable_assignment": "block = ['--- /dev/null\\n', '+++ file.txt\\n', '@@ ... @@\\n', '-Original\\n', '+Modified\\n']", "loop_range": [2, 5], "post_loop_line": 7} {"idx": 15, "scratchpad_format": "def _test_grad_nd(n, ndim):\n coords = [np.arange(n)] * ndim # [STATE] coords = [array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91])] [/STATE]\n xc = np.meshgrid(*coords, indexing=\"ij\") # [STATE] xc = [array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91])] [/STATE]\n\n # u = sum_i(xc[i]**2)\n u = reduce(lambda x,y: x+y**2, xc, 0.0) # [STATE] u = array([0.000e+00, 1.000e+00, 4.000e+00, 9.000e+00, 1.600e+01, 2.500e+01, 3.600e+01, 4.900e+01, 6.400e+01, 8.100e+01, 1.000e+02, 1.210e+02, 1.440e+02, 1.690e+02, 1.960e+02, 2.250e+02, 2.560e+02, 2.890e+02, 3.240e+02, 3.610e+02, 4.000e+02, 4.410e+02, 4.840e+02, 5.290e+02, 5.760e+02, 6.250e+02, 6.760e+02, 7.290e+02, 7.840e+02, 8.410e+02, 9.000e+02, 9.610e+02, 1.024e+03, 1.089e+03, 1.156e+03, 1.225e+03, 1.296e+03, 1.369e+03, 1.444e+03, 1.521e+03, 1.600e+03, 1.681e+03, 1.764e+03, 1.849e+03, 1.936e+03, 2.025e+03, 2.116e+03, 2.209e+03, 2.304e+03, 2.401e+03, 2.500e+03, 2.601e+03, 2.704e+03, 2.809e+03, 2.916e+03, 3.025e+03, 3.136e+03, 3.249e+03, 3.364e+03, 3.481e+03, 3.600e+03, 3.721e+03, 3.844e+03, 3.969e+03, 4.096e+03, 4.225e+03, 4.356e+03, 4.489e+03, 4.624e+03, 4.761e+03, 4.900e+03, 5.041e+03, 5.184e+03, 5.329e+03, 5.476e+03, 5.625e+03, 5.776e+03, 5.929e+03, 6.084e+03, 6.241e+03, 6.400e+03, 6.561e+03, 6.724e+03, 6.889e+03, 7.056e+03, 7.225e+03, 7.396e+03, 7.569e+03, 7.744e+03, 7.921e+03, 8.100e+03, 8.281e+03]) [/STATE]\n ucopy = np.copy(u) # [STATE] ucopy = array([0.000e+00, 1.000e+00, 4.000e+00, 9.000e+00, 1.600e+01, 2.500e+01, 3.600e+01, 4.900e+01, 6.400e+01, 8.100e+01, 1.000e+02, 1.210e+02, 1.440e+02, 1.690e+02, 1.960e+02, 2.250e+02, 2.560e+02, 2.890e+02, 3.240e+02, 3.610e+02, 4.000e+02, 4.410e+02, 4.840e+02, 5.290e+02, 5.760e+02, 6.250e+02, 6.760e+02, 7.290e+02, 7.840e+02, 8.410e+02, 9.000e+02, 9.610e+02, 1.024e+03, 1.089e+03, 1.156e+03, 1.225e+03, 1.296e+03, 1.369e+03, 1.444e+03, 1.521e+03, 1.600e+03, 1.681e+03, 1.764e+03, 1.849e+03, 1.936e+03, 2.025e+03, 2.116e+03, 2.209e+03, 2.304e+03, 2.401e+03, 2.500e+03, 2.601e+03, 2.704e+03, 2.809e+03, 2.916e+03, 3.025e+03, 3.136e+03, 3.249e+03, 3.364e+03, 3.481e+03, 3.600e+03, 3.721e+03, 3.844e+03, 3.969e+03, 4.096e+03, 4.225e+03, 4.356e+03, 4.489e+03, 4.624e+03, 4.761e+03, 4.900e+03, 5.041e+03, 5.184e+03, 5.329e+03, 5.476e+03, 5.625e+03, 5.776e+03, 5.929e+03, 6.084e+03, 6.241e+03, 6.400e+03, 6.561e+03, 6.724e+03, 6.889e+03, 7.056e+03, 7.225e+03, 7.396e+03, 7.569e+03, 7.744e+03, 7.921e+03, 8.100e+03, 8.281e+03]) [/STATE]\n\n # check the gradient values\n slices = tuple([slice(1,-1,None)] * ndim) # [STATE] slices = (slice(1, -1, None),) [/STATE]\n for i in range(ndim): # [STATE] i = 0 [/STATE]\n assert grad(u, axis=i) == pytest.approx(2*xc[i][slices]) # [STATE] @py_assert3 = None [/STATE] # [STATE] @py_assert7 = None [/STATE] # [STATE] @py_assert9 = None [/STATE] # [STATE] @py_assert11 = None [/STATE] # [STATE] @py_assert13 = None [/STATE] # [STATE] @py_assert14 = None [/STATE] # [STATE] @py_assert5 = None [/STATE]\n\n # check if u is unchanged\n assert np.all(u == ucopy) # [STATE] @py_assert1 = None [/STATE] # [STATE] @py_assert4 = None [/STATE] # [STATE] @py_assert8 = None [/STATE]\n\n_test_grad_nd(92, 1)", "loop_code": "1: def _test_grad_nd(n, ndim):\n2: coords = [np.arange(n)] * ndim\n3: xc = np.meshgrid(*coords, indexing=\"ij\")\n4:\n5: # u = sum_i(xc[i]**2)\n6: u = reduce(lambda x,y: x+y**2, xc, 0.0)\n7: ucopy = np.copy(u)\n8:\n9: # check the gradient values\n10: slices = tuple([slice(1,-1,None)] * ndim)\n11: for i in range(ndim):\n12: assert grad(u, axis=i) == pytest.approx(2*xc[i][slices])\n13:\n14: # check if u is unchanged\n15: assert np.all(u == ucopy)\n16:\n17: _test_grad_nd(92, 1)", "question": "What is the value of '@py_assert8' in line 15 after executing '_test_grad_nd(92, 1)'?", "answer": "None", "variable_assignment": "@py_assert8 = None", "loop_range": [11, 12], "post_loop_line": 15} {"idx": 16, "scratchpad_format": "def _test_grad2_nd(n, ndim):\n coords = [np.arange(n)] * ndim # [STATE] coords = [array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])] [/STATE]\n xc = np.meshgrid(*coords, indexing=\"ij\") # [STATE] xc = [array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])] [/STATE]\n\n # u = sum_i(xc[i]**2)\n u = reduce(lambda x,y: x+y**2, xc, 0.0) # [STATE] u = array([ 0., 1., 4., 9., 16., 25., 36., 49., 64., 81., 100., 121., 144., 169., 196., 225., 256., 289., 324., 361., 400., 441., 484., 529., 576., 625., 676., 729., 784., 841., 900., 961.]) [/STATE]\n ucopy = np.copy(u) # [STATE] ucopy = array([ 0., 1., 4., 9., 16., 25., 36., 49., 64., 81., 100., 121., 144., 169., 196., 225., 256., 289., 324., 361., 400., 441., 484., 529., 576., 625., 676., 729., 784., 841., 900., 961.]) [/STATE]\n\n # check the gradient values\n gu = np.zeros(tuple([n-2]*ndim)) # [STATE] gu = array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]) [/STATE]\n gu2 = gu + 2.0 # [STATE] gu2 = array([2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.]) [/STATE]\n for i in range(ndim): # [STATE] i = 0 [/STATE]\n for j in range(ndim): # [STATE] j = 0 [/STATE]\n if i == j:\n assert grad2(u, axes=(i,j)) == pytest.approx(gu2) # [STATE] @py_assert2 = None [/STATE] # [STATE] @py_assert4 = None [/STATE] # [STATE] @py_assert8 = None [/STATE] # [STATE] @py_assert11 = None [/STATE] # [STATE] @py_assert6 = None [/STATE]\n else:\n assert grad2(u, axes=(i,j)) == pytest.approx(gu)\n\n # check if u is unchanged\n assert np.all(u == ucopy) # [STATE] @py_assert1 = None [/STATE]\n\n_test_grad2_nd(32, 1)", "loop_code": "1: def _test_grad2_nd(n, ndim):\n2: coords = [np.arange(n)] * ndim\n3: xc = np.meshgrid(*coords, indexing=\"ij\")\n4:\n5: # u = sum_i(xc[i]**2)\n6: u = reduce(lambda x,y: x+y**2, xc, 0.0)\n7: ucopy = np.copy(u)\n8:\n9: # check the gradient values\n10: gu = np.zeros(tuple([n-2]*ndim))\n11: gu2 = gu + 2.0\n12: for i in range(ndim):\n13: for j in range(ndim):\n14: if i == j:\n15: assert grad2(u, axes=(i,j)) == pytest.approx(gu2)\n16: else:\n17: assert grad2(u, axes=(i,j)) == pytest.approx(gu)\n18:\n19: # check if u is unchanged\n20: assert np.all(u == ucopy)\n21:\n22: _test_grad2_nd(32, 1)", "question": "What is the value of '@py_assert1' in line 20 after executing '_test_grad2_nd(32, 1)'?", "answer": "None", "variable_assignment": "@py_assert1 = None", "loop_range": [12, 17], "post_loop_line": 20} {"idx": 17, "scratchpad_format": "def test_audioclip_stereo_max_volume(nchannels, channel_muted):\n def make_frame(t): # [STATE] make_frame = .make_frame at 0x7f8c02a8e670> [/STATE]\n frame = []\n # build channels (one of each pair muted)\n for i in range(int(nchannels / 2)):\n if channel_muted == \"left\":\n # if muted channel is left, [0, sound, 0, sound...]\n frame.append(np.sin(t * 0))\n frame.append(np.sin(440 * 2 * np.pi * t))\n else:\n # if muted channel is right, [sound, 0, sound, 0...]\n frame.append(np.sin(440 * 2 * np.pi * t))\n frame.append(np.sin(t * 0))\n return np.array(frame).T\n\n clip = AudioClip(make_frame, fps=44100, duration=1) # [STATE] clip = {start=0, end=1, duration=1, memoize=False, memoized_t=None, memoized_frame=None, fps=44100, nchannels=2} [/STATE]\n max_volume = clip.max_volume(stereo=True) # [STATE] max_volume = array([0. , 0.99999975]) [/STATE]\n # if `stereo == True`, `AudioClip.max_volume` returns a Numpy array`\n assert isinstance(max_volume, np.ndarray) # [STATE] @py_assert3 = None [/STATE] # [STATE] @py_assert5 = None [/STATE]\n assert len(max_volume) == nchannels # [STATE] @py_assert2 = None [/STATE] # [STATE] @py_assert4 = None [/STATE]\n\n # check channels muted and with sound\n for i, channel_max_volume in enumerate(max_volume): # [STATE] i = 0 [/STATE] [STATE] channel_max_volume = 0.0 [/STATE] [STATE] i = 1 [/STATE] [STATE] channel_max_volume = 0.999999746257887 [/STATE]\n if i % 2 == 0:\n if channel_muted == \"left\":\n assert channel_max_volume == 0 # [STATE] @py_assert1 = None [/STATE]\n else:\n assert channel_max_volume > 0\n else:\n if channel_muted == \"right\":\n assert channel_max_volume == 0\n else:\n assert channel_max_volume > 0\n\ntest_audioclip_stereo_max_volume(2, 'left')", "loop_code": "1: def test_audioclip_stereo_max_volume(nchannels, channel_muted):\n2: def make_frame(t):\n3: frame = []\n4: # build channels (one of each pair muted)\n5: for i in range(int(nchannels / 2)):\n6: if channel_muted == \"left\":\n7: # if muted channel is left, [0, sound, 0, sound...]\n8: frame.append(np.sin(t * 0))\n9: frame.append(np.sin(440 * 2 * np.pi * t))\n10: else:\n11: # if muted channel is right, [sound, 0, sound, 0...]\n12: frame.append(np.sin(440 * 2 * np.pi * t))\n13: frame.append(np.sin(t * 0))\n14: return np.array(frame).T\n15:\n16: clip = AudioClip(make_frame, fps=44100, duration=1)\n17: max_volume = clip.max_volume(stereo=True)\n18: # if `stereo == True`, `AudioClip.max_volume` returns a Numpy array`\n19: assert isinstance(max_volume, np.ndarray)\n20: assert len(max_volume) == nchannels\n21:\n22: # check channels muted and with sound\n23: for i, channel_max_volume in enumerate(max_volume):\n24: if i % 2 == 0:\n25: if channel_muted == \"left\":\n26: assert channel_max_volume == 0\n27: else:\n28: assert channel_max_volume > 0\n29: else:\n30: if channel_muted == \"right\":\n31: assert channel_max_volume == 0\n32: else:\n33: assert channel_max_volume > 0\n34:\n35: test_audioclip_stereo_max_volume(2, 'left')", "question": "What is the value of 'clip' in line 16 after executing 'test_audioclip_stereo_max_volume(2, 'left')'?", "answer": "{start=0, end=1, duration=1, memoize=False, memoized_t=None, memoized_frame=None, fps=44100, nchannels=2}", "variable_assignment": "clip = {start=0, end=1, duration=1, memoize=False, memoized_t=None, memoized_frame=None, fps=44100, nchannels=2}", "loop_range": [5, 13], "post_loop_line": 16} {"idx": 18, "scratchpad_format": "def version_compare(v1, v2):\n \"\"\"Returns -1 if v1 is older than v2, 0 if v1 == v2, and +1 if v1 > v2.\"\"\"\n\n arr1 = v1.split(\".\") # [STATE] arr1 = ['3', '8', '18'] [/STATE]\n arr2 = v2.split(\".\") # [STATE] arr2 = ['3', '8', '27'] [/STATE]\n n = len(arr1) # [STATE] n = 3 [/STATE]\n m = len(arr2) # [STATE] m = 3 [/STATE]\n\n # converts to integer from string\n arr1 = [int(i) for i in arr1] # [STATE] arr1 = [3, 8, 18] [/STATE]\n arr2 = [int(i) for i in arr2] # [STATE] arr2 = [3, 8, 27] [/STATE]\n\n # compares which list is bigger and fills\n # smaller list with zero (for unequal delimeters)\n if n > m:\n for i in range(m, n):\n arr2.append(0)\n elif m > n:\n for i in range(n, m):\n arr1.append(0)\n\n # returns 1 if version 1 is bigger and -1 if\n # version 2 is bigger and 0 if equal\n for i in range(len(arr1)): # [STATE] i = 0 [/STATE] [STATE] i = 1 [/STATE] [STATE] i = 2 [/STATE]\n if arr1[i] > arr2[i]:\n return 1\n elif arr2[i] > arr1[i]:\n return -1\n return 0\n\nversion_compare('3.8.18', '3.8.27')", "loop_code": "1: def version_compare(v1, v2):\n2: \"\"\"Returns -1 if v1 is older than v2, 0 if v1 == v2, and +1 if v1 > v2.\"\"\"\n3:\n4: arr1 = v1.split(\".\")\n5: arr2 = v2.split(\".\")\n6: n = len(arr1)\n7: m = len(arr2)\n8:\n9: # converts to integer from string\n10: arr1 = [int(i) for i in arr1]\n11: arr2 = [int(i) for i in arr2]\n12:\n13: # compares which list is bigger and fills\n14: # smaller list with zero (for unequal delimeters)\n15: if n > m:\n16: for i in range(m, n):\n17: arr2.append(0)\n18: elif m > n:\n19: for i in range(n, m):\n20: arr1.append(0)\n21:\n22: # returns 1 if version 1 is bigger and -1 if\n23: # version 2 is bigger and 0 if equal\n24: for i in range(len(arr1)):\n25: if arr1[i] > arr2[i]:\n26: return 1\n27: elif arr2[i] > arr1[i]:\n28: return -1\n29: return 0\n30:\n31: version_compare('3.8.18', '3.8.27')", "question": "What is the value of 'i' in line 24 after executing 'version_compare('3.8.18', '3.8.27')'?", "answer": "2", "variable_assignment": "i = 2", "loop_range": [19, 20], "post_loop_line": 24} {"idx": 19, "scratchpad_format": "def _validate_htype_overwrites(htype: str, htype_overwrite: dict):\n \"\"\"Raises errors if ``htype_overwrite`` has invalid keys or was missing required values.\"\"\"\n\n defaults = HTYPE_CONFIGURATIONS[htype] # [STATE] defaults = {'dtype': None, 'sample_compression': None, 'chunk_compression': None, 'typestr': None, 'max_chunk_size': None, 'tiling_threshold': None, 'is_sequence': False, 'is_link': False, 'hidden': False, 'links': None, 'verify': False} [/STATE]\n\n for key, value in htype_overwrite.items(): # [STATE] key = 'sample_compression' [/STATE] [STATE] value = 'unspecified' [/STATE] [STATE] key = 'chunk_compression' [/STATE] [STATE] key = 'dtype' [/STATE] [STATE] value = 'int64' [/STATE] [STATE] key = 'hidden' [/STATE] [STATE] value = True [/STATE] [STATE] key = 'max_chunk_size' [/STATE] [STATE] value = 4000000 [/STATE] [STATE] key = 'is_sequence' [/STATE] [STATE] value = False [/STATE] [STATE] key = 'is_link' [/STATE] [STATE] key = 'verify' [/STATE]\n if key not in defaults:\n raise TensorMetaInvalidHtypeOverwriteKey(htype, key, list(defaults.keys()))\n\n if isinstance(value, str) and value == UNSPECIFIED:\n if defaults[key] == REQUIRE_USER_SPECIFICATION:\n raise TensorMetaMissingRequiredValue(htype, key)\n\n sc = htype_overwrite[\"sample_compression\"] # [STATE] sc = 'unspecified' [/STATE]\n cc = htype_overwrite[\"chunk_compression\"] # [STATE] cc = 'unspecified' [/STATE]\n compr = sc if cc in (None, UNSPECIFIED) else cc # [STATE] compr = 'unspecified' [/STATE]\n actual_htype = f\"link[{htype}]\" if htype_overwrite[\"is_link\"] else htype # [STATE] actual_htype = 'generic' [/STATE]\n if htype.startswith(\"image\") and sc == UNSPECIFIED and cc == UNSPECIFIED:\n raise TensorMetaMissingRequiredValue(\n actual_htype, [\"chunk_compression\", \"sample_compression\"] # type: ignore\n )\n if htype in (\"audio\", \"video\", \"point_cloud\", \"mesh\", \"nifti\"):\n if cc not in (UNSPECIFIED, None):\n raise UnsupportedCompressionError(\"Chunk compression\", htype=htype)\n elif sc == UNSPECIFIED:\n raise TensorMetaMissingRequiredValue(\n actual_htype, \"sample_compression\" # type: ignore\n )\n supported_compressions = HTYPE_SUPPORTED_COMPRESSIONS.get(htype) # [STATE] supported_compressions = None [/STATE]\n if (\n compr\n and compr != UNSPECIFIED\n and supported_compressions\n and compr not in supported_compressions\n ):\n raise UnsupportedCompressionError(compr, htype=htype)\n\n_validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})", "loop_code": "1: def _validate_htype_overwrites(htype: str, htype_overwrite: dict):\n2: \"\"\"Raises errors if ``htype_overwrite`` has invalid keys or was missing required values.\"\"\"\n3:\n4: defaults = HTYPE_CONFIGURATIONS[htype]\n5:\n6: for key, value in htype_overwrite.items():\n7: if key not in defaults:\n8: raise TensorMetaInvalidHtypeOverwriteKey(htype, key, list(defaults.keys()))\n9:\n10: if isinstance(value, str) and value == UNSPECIFIED:\n11: if defaults[key] == REQUIRE_USER_SPECIFICATION:\n12: raise TensorMetaMissingRequiredValue(htype, key)\n13:\n14: sc = htype_overwrite[\"sample_compression\"]\n15: cc = htype_overwrite[\"chunk_compression\"]\n16: compr = sc if cc in (None, UNSPECIFIED) else cc\n17: actual_htype = f\"link[{htype}]\" if htype_overwrite[\"is_link\"] else htype\n18: if htype.startswith(\"image\") and sc == UNSPECIFIED and cc == UNSPECIFIED:\n19: raise TensorMetaMissingRequiredValue(\n20: actual_htype, [\"chunk_compression\", \"sample_compression\"] # type: ignore\n21: )\n22: if htype in (\"audio\", \"video\", \"point_cloud\", \"mesh\", \"nifti\"):\n23: if cc not in (UNSPECIFIED, None):\n24: raise UnsupportedCompressionError(\"Chunk compression\", htype=htype)\n25: elif sc == UNSPECIFIED:\n26: raise TensorMetaMissingRequiredValue(\n27: actual_htype, \"sample_compression\" # type: ignore\n28: )\n29: supported_compressions = HTYPE_SUPPORTED_COMPRESSIONS.get(htype)\n30: if (\n31: compr\n32: and compr != UNSPECIFIED\n33: and supported_compressions\n34: and compr not in supported_compressions\n35: ):\n36: raise UnsupportedCompressionError(compr, htype=htype)\n37:\n38: _validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})", "question": "What is the value of 'sc' in line 14 after executing '_validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})'?", "answer": "'unspecified'", "variable_assignment": "sc = 'unspecified'", "loop_range": [6, 12], "post_loop_line": 14} {"idx": 20, "scratchpad_format": "def format_uptime(uptime_in_seconds):\n \"\"\"Format number of seconds into human-readable string.\n\n :param uptime_in_seconds: The server uptime in seconds.\n :returns: A human-readable string representing the uptime.\n\n >>> uptime = format_uptime('56892')\n >>> print(uptime)\n 15 hours 48 min 12 sec\n \"\"\"\n\n m, s = divmod(int(uptime_in_seconds), 60) # [STATE] m = 0 [/STATE] # [STATE] s = 59 [/STATE]\n h, m = divmod(m, 60) # [STATE] h = 0 [/STATE]\n d, h = divmod(h, 24) # [STATE] d = 0 [/STATE]\n\n uptime_values = [] # [STATE] uptime_values = [] [/STATE]\n\n for value, unit in ((d, 'days'), (h, 'hours'), (m, 'min'), (s, 'sec')): # [STATE] value = 0 [/STATE] [STATE] unit = 'days' [/STATE] [STATE] unit = 'hours' [/STATE] [STATE] unit = 'min' [/STATE] [STATE] value = 59 [/STATE] [STATE] unit = 'sec' [/STATE]\n if value == 0 and not uptime_values:\n # Don't include a value/unit if the unit isn't applicable to\n # the uptime. E.g. don't do 0 days 0 hours 1 min 30 sec.\n continue\n elif value == 1 and unit.endswith('s'):\n # Remove the \"s\" if the unit is singular.\n unit = unit[:-1]\n uptime_values.append('{0} {1}'.format(value, unit)) # [STATE] uptime_values = ['59 sec'] [/STATE]\n\n uptime = ' '.join(uptime_values) # [STATE] uptime = '59 sec' [/STATE]\n return uptime\n\nformat_uptime(59)", "loop_code": "1: def format_uptime(uptime_in_seconds):\n2: \"\"\"Format number of seconds into human-readable string.\n3:\n4: :param uptime_in_seconds: The server uptime in seconds.\n5: :returns: A human-readable string representing the uptime.\n6:\n7: >>> uptime = format_uptime('56892')\n8: >>> print(uptime)\n9: 15 hours 48 min 12 sec\n10: \"\"\"\n11:\n12: m, s = divmod(int(uptime_in_seconds), 60)\n13: h, m = divmod(m, 60)\n14: d, h = divmod(h, 24)\n15:\n16: uptime_values = []\n17:\n18: for value, unit in ((d, 'days'), (h, 'hours'), (m, 'min'), (s, 'sec')):\n19: if value == 0 and not uptime_values:\n20: # Don't include a value/unit if the unit isn't applicable to\n21: # the uptime. E.g. don't do 0 days 0 hours 1 min 30 sec.\n22: continue\n23: elif value == 1 and unit.endswith('s'):\n24: # Remove the \"s\" if the unit is singular.\n25: unit = unit[:-1]\n26: uptime_values.append('{0} {1}'.format(value, unit))\n27:\n28: uptime = ' '.join(uptime_values)\n29: return uptime\n30:\n31: format_uptime(59)", "question": "What is the value of 'uptime' in line 28 after executing 'format_uptime(59)'?", "answer": "'59 sec'", "variable_assignment": "uptime = '59 sec'", "loop_range": [18, 26], "post_loop_line": 28} {"idx": 21, "scratchpad_format": "def run_neox_args_load_test(yaml_files):\n from megatron.neox_arguments import NeoXArgs # [STATE] NeoXArgs = [/STATE]\n\n yaml_list = get_configs_with_path(yaml_files) # [STATE] yaml_list = ['/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/125M.yml', '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/local_setup.yml', '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/cpu_mock_config.yml'] [/STATE]\n args_loaded = NeoXArgs.from_ymls(yaml_list) # [STATE] args_loaded = NeoXArgs(distributed_backend='nccl', local_rank=None, rank=None, lazy_mpu_init=False, short_seq_prob=0.1, eod_mask_loss=False, adlr_autoresume=False, adlr_autoresume_interval=1000, seed=1234, onnx_safe=False, deepscale=False, deepscale_config=None, deepspeed_mpi=False, deepspeed_slurm=False, user_script=None, iteration=None, do_train=None, do_valid=None, do_test=None, save_iters=[10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, 100000, 110000, 120000, 130000, 140000, 150000, 160000, 170000, 180000, 190000, 200000, 210000, 220000, 230000, 240000, 250000, 260000, 270000, 280000, 290000, 300000, 310000], global_num_gpus=1, text_gen_type='unconditional', temperature=0.0, top_p=0.0, top_k=0, return_logits=False, maximum_tokens=64, prompt_end='\\n', sample_input_file=None, sample_output_file='samples.txt', num_samples=1, recompute=False, eval_results_prefix='', eval_tasks=None, use_wandb=True, wandb_group=None, wandb_team=None, wandb_project='neox', wandb_host='https://api.wandb.ai', wandb_init_all_ranks=False, git_hash='7a8fa2f0', log_dir='logs', tensorboard_dir='tensorboard', log_interval=100, log_grad_pct_zeros=False, log_param_norm=False, log_grad_norm=False, log_optimizer_states=False, log_gradient_noise_scale=False, gradient_noise_scale_n_batches=5, gradient_noise_scale_cpu_offload=False, pipe_parallel_size=1, model_parallel_size=1, pipe_partition_method='type:transformer|mlp', world_size=None, is_pipe_parallel=True, data_path='data/enwik8/enwik8_text_document', use_shared_fs=True, train_data_paths=None, label_data_paths=None, test_data_paths=None, valid_data_paths=None, train_data_weights=None, valid_data_weights=None, test_data_weights=None, weight_by_num_documents=False, weighted_sampler_alpha=1.0, data_impl='mmap', mmap_warmup=False, save='checkpoints', s3_path=None, s3_chunk_size=104857600, config_files={'125M.yml': '# GPT-2 pretraining setup\\n{\\n # parallelism settings ( you will want to change these based on your cluster setup, ideally scheduling pipeline stages\\n # across the node boundaries )\\n \"pipe_parallel_size\": 1,\\n \"model_parallel_size\": 1,\\n\\n # model settings\\n \"num_layers\": 12,\\n \"hidden_size\": 768,\\n \"num_attention_heads\": 12,\\n \"seq_length\": 2048,\\n \"max_position_embeddings\": 2048,\\n \"norm\": \"layernorm\",\\n \"pos_emb\": \"rotary\",\\n \"no_weight_tying\": true,\\n \"gpt_j_residual\": false,\\n \"output_layer_parallelism\": \"column\",\\n\\n # these should provide some speedup but takes a while to build, set to true if desired\\n \"scaled_upper_triang_masked_softmax_fusion\": false,\\n \"bias_gelu_fusion\": false,\\n \"rope_fusion\": false,\\n\\n # init methods\\n \"init_method\": \"small_init\",\\n \"output_layer_init_method\": \"wang_init\",\\n\\n\\n # optimizer settings\\n \"optimizer\": {\\n \"type\": \"Adam\",\\n \"params\": {\\n \"lr\": 0.0006,\\n \"betas\": [0.9, 0.95],\\n \"eps\": 1.0e-8,\\n }\\n },\\n \"min_lr\": 0.00006,\\n\\n # for all zero_optimization options, see https://www.deepspeed.ai/docs/config-json/#zero-optimizations-for-fp16-training\\n \"zero_optimization\": {\\n \"stage\": 1,\\n \"allgather_partitions\": True,\\n \"allgather_bucket_size\": 500000000,\\n \"overlap_comm\": True,\\n \"reduce_scatter\": True,\\n \"reduce_bucket_size\": 500000000,\\n \"contiguous_gradients\": True,\\n },\\n\\n # batch / data settings\\n \"train_micro_batch_size_per_gpu\": 4,\\n \"data_impl\": \"mmap\",\\n\\n # activation checkpointing\\n \"checkpoint_activations\": true,\\n \"checkpoint_num_layers\": 1,\\n \"partition_activations\": true,\\n \"synchronize_each_layer\": true,\\n\\n # regularization\\n \"gradient_clipping\": 1.0,\\n \"weight_decay\": 0.1,\\n \"hidden_dropout\": 0.0,\\n \"attention_dropout\": 0.0,\\n\\n # precision settings\\n \"fp16\": {\\n \"enabled\": true,\\n \"loss_scale\": 0,\\n \"loss_scale_window\": 1000,\\n \"hysteresis\": 2,\\n \"min_loss_scale\": 1\\n },\\n\\n # misc. training settings\\n \"train_iters\": 320000,\\n \"lr_decay_iters\": 320000,\\n \"distributed_backend\": \"nccl\",\\n \"lr_decay_style\": \"cosine\",\\n \"warmup\": 0.01,\\n \"checkpoint_factor\": 10...\\n{\\n \"global_num_gpus\": 1\\n}\\n'}, load='checkpoints', checkpoint_validation_with_forward_pass=False, checkpoint_scale='linear', checkpoint_factor=10000, extra_save_iters=None, no_save_optim=False, no_save_rng=False, no_load_optim=False, no_load_rng=False, finetune=False, batch_size=4, train_iters=320000, eval_iters=10, keep_last_n_checkpoints=4, eval_interval=1000, split='969, 30, 1', vocab_file='data/gpt2-vocab.json', merge_file='data/gpt2-merges.txt', num_workers=2, exit_interval=None, attention_dropout=0.0, hidden_dropout=0.0, weight_decay=0.1, checkpoint_activations=True, checkpoint_num_layers=1, deepspeed_activation_checkpointing=True, contiguous_checkpointing=False, checkpoint_in_cpu=False, synchronize_each_layer=True, profile_backward=False, partition_activations=True, gas=1, clip_grad=1.0, hysteresis=2, dynamic_loss_scale=True, loss_scale=None, loss_scale_window=1000.0, min_scale=1.0, char_level_ppl=False, use_mup=False, coord_check=False, save_base_shapes=False, base_shapes_file=None, mup_init_scale=1.0, mup_attn_temp=1.0, mup_output_temp=1.0, mup_embedding_mult=1.0, mup_rp_embedding_mult=1.0, mup_width_scale=2, tokenizer_type='GPT2BPETokenizer', padded_vocab_size=None, optimizer_type='Adam', use_bnb_optimizer=False, zero_stage=1, zero_reduce_scatter=True, zero_contiguous_gradients=True, zero_reduce_bucket_size=500000000, zero_allgather_bucket_size=500000000, lr=0.0006, lr_decay_style='cosine', lr_decay_iters=320000, min_lr=6e-05, warmup=0.01, override_lr_scheduler=False, use_checkpoint_lr_scheduler=False, precision='fp16', num_layers=12, hidden_size=768, num_attention_heads=12, seq_length=2048, max_position_embeddings=2048, norm='layernorm', use_qk_layernorm=False, layernorm_epsilon=1e-05, rms_norm_epsilon=1e-08, scalenorm_epsilon=1e-08, pos_emb='rotary', rpe_num_buckets=32, rpe_max_distance=128, opt_pos_emb_offset=0, no_weight_tying=True, attention_config=['global', 'global', 'global', 'global', 'global', 'global', 'global', 'global', 'global', 'global', 'global', 'global'], sparsity_config={}, num_unique_layers=None, param_sharing_style='grouped', make_vocab_size_divisible_by=128, activation='gelu', scaled_upper_triang_masked_softmax_fusion=False, scaled_masked_softmax_fusion=False, bias_gelu_fusion=False, bias_dropout_fusion=False, rope_fusion=False, fp16_lm_cross_entropy=False, init_method_std=0.02, apply_query_key_layer_scaling=False, use_cpu_initialization=False, attention_softmax_in_fp32=False, rotary_pct=1.0, rotary_emb_base=10000, init_method='small_init', output_layer_init_method='wang_init', gmlp_attn_dim=64, gpt_j_residual=False, gpt_j_tied=False, use_bias_in_norms=True, use_bias_in_attn_linear=True, mlp_type='regular', soft_prompt_tuning=None, output_layer_parallelism='column', deepspeed=True, train_batch_size=4, train_micro_batch_size_per_gpu=4, gradient_accumulation_steps=1, optimizer={'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}, scheduler=None, fp32_allreduce=False, prescale_gradients=False, gradient_predivide_factor=1.0, sparse_gradients=False, fp16={'enabled': True, 'loss_scale': 0, 'loss_scale_window': 1000, 'hysteresis': 2, 'min_loss_scale': 1}, bf16=None, amp=None, gradient_clipping=1.0, zero_optimization={'stage': 1, 'allgather_partitions': True, 'allgather_bucket_size': 500000000, 'overlap_comm': True, 'reduce_scatter': True, 'reduce_bucket_size': 500000000, 'contiguous_gradients': True}, curriculum_learning=None, curriculum_seqlen=0, steps_per_print=10, wall_clock_breakdown=True, dump_state=False, flops_profiler=None, communication_data_type=None, autotuning=None, activation_checkpointing=None, sparse_attention=None, data_efficiency=None, tensorboard=None, wandb=None, csv_monitor=None, elasticity=None, comms_logger=None, compression_training=None, checkpoint=None, data_types=None, deepspeed_extra_args=None, hostfile='/mock_path', include=None, exclude=None, num_nodes=-1, num_gpus=None, master_port=29500, master_addr=None, launcher='pdsh', force_multi=False, detect_nvlink_pairs=False, autotuning_run=None, no_ssh_check=False, comment=None, account=None) [/STATE]\n assert isinstance(args_loaded, NeoXArgs) # [STATE] @py_assert3 = None [/STATE]\n\n # initialize an empty config dictionary to be filled by yamls\n config = dict() # [STATE] config = {} [/STATE]\n\n # iterate of all to be loaded yaml files\n for conf_file_name in yaml_list: # [STATE] conf_file_name = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/125M.yml' [/STATE] [STATE] conf_file_name = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/local_setup.yml' [/STATE] [STATE] conf_file_name = '/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/cpu_mock_config.yml' [/STATE]\n\n # load file\n with open(conf_file_name) as conf_file: # [STATE] conf_file = <_io.TextIOWrapper name='/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/125M.yml' mode='r' encoding='UTF-8'> [/STATE] [STATE] conf_file = <_io.TextIOWrapper name='/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/local_setup.yml' mode='r' encoding='UTF-8'> [/STATE] [STATE] conf_file = <_io.TextIOWrapper name='/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/EleutherAI+gpt-neox/EleutherAI+gpt-neox/configs/cpu_mock_config.yml' mode='r' encoding='UTF-8'> [/STATE]\n conf = yaml.load(conf_file, Loader=yaml.FullLoader) # [STATE] conf = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init', 'optimizer': {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}, 'min_lr': 6e-05, 'zero_optimization': {'stage': 1, 'allgather_partitions': True, 'allgather_bucket_size': 500000000, 'overlap_comm': True, 'reduce_scatter': True, 'reduce_bucket_size': 500000000, 'contiguous_gradients': True}, 'train_micro_batch_size_per_gpu': 4, 'data_impl': 'mmap', 'checkpoint_activations': True, 'checkpoint_num_layers': 1, 'partition_activations': True, 'synchronize_each_layer': True, 'gradient_clipping': 1.0, 'weight_decay': 0.1, 'hidden_dropout': 0.0, 'attention_dropout': 0.0, 'fp16': {'enabled': True, 'loss_scale': 0, 'loss_scale_window': 1000, 'hysteresis': 2, 'min_loss_scale': 1}, 'train_iters': 320000, 'lr_decay_iters': 320000, 'distributed_backend': 'nccl', 'lr_decay_style': 'cosine', 'warmup': 0.01, 'checkpoint_factor': 10000, 'eval_interval': 1000, 'eval_iters': 10, 'log_interval': 100, 'steps_per_print': 10, 'keep_last_n_checkpoints': 4, 'wall_clock_breakdown': True, 'hostfile': '/mock_path'} [/STATE] [STATE] conf = {'data_path': 'data/enwik8/enwik8_text_document', 'vocab_file': 'data/gpt2-vocab.json', 'merge_file': 'data/gpt2-merges.txt', 'save': 'checkpoints', 'load': 'checkpoints', 'checkpoint_validation_with_forward_pass': False, 'tensorboard_dir': 'tensorboard', 'log_dir': 'logs', 'use_wandb': True, 'wandb_host': 'https://api.wandb.ai', 'wandb_project': 'neox'} [/STATE] [STATE] conf = {'global_num_gpus': 1} [/STATE]\n\n # check for key duplicates and load values\n for conf_key, conf_value in conf.items(): # [STATE] conf_key = 'pipe_parallel_size' [/STATE] [STATE] conf_value = 1 [/STATE] [STATE] conf_key = 'model_parallel_size' [/STATE] [STATE] conf_key = 'num_layers' [/STATE] [STATE] conf_value = 12 [/STATE] [STATE] conf_key = 'hidden_size' [/STATE] [STATE] conf_value = 768 [/STATE] [STATE] conf_key = 'num_attention_heads' [/STATE] [STATE] conf_key = 'seq_length' [/STATE] [STATE] conf_value = 2048 [/STATE] [STATE] conf_key = 'max_position_embeddings' [/STATE] [STATE] conf_key = 'norm' [/STATE] [STATE] conf_value = 'layernorm' [/STATE] [STATE] conf_key = 'pos_emb' [/STATE] [STATE] conf_value = 'rotary' [/STATE] [STATE] conf_key = 'no_weight_tying' [/STATE] [STATE] conf_value = True [/STATE] [STATE] conf_key = 'gpt_j_residual' [/STATE] [STATE] conf_value = False [/STATE] [STATE] conf_key = 'output_layer_parallelism' [/STATE] [STATE] conf_value = 'column' [/STATE]\n if conf_key in config:\n raise ValueError(\n f\"Conf file {conf_file_name} has the following duplicate keys with previously loaded file: {conf_key}\"\n )\n\n conf_key_converted = conf_key.replace( # [STATE] conf_key_converted = 'pipe_parallel_size' [/STATE] [STATE] conf_key_converted = 'model_parallel_size' [/STATE] [STATE] conf_key_converted = 'num_layers' [/STATE] [STATE] conf_key_converted = 'hidden_size' [/STATE] [STATE] conf_key_converted = 'num_attention_heads' [/STATE] [STATE] conf_key_converted = 'seq_length' [/STATE] [STATE] conf_key_converted = 'max_position_embeddings' [/STATE] [STATE] conf_key_converted = 'norm' [/STATE] [STATE] conf_key_converted = 'pos_emb' [/STATE] [STATE] conf_key_converted = 'no_weight_tying' [/STATE] [STATE] conf_key_converted = 'gpt_j_residual' [/STATE] [STATE] conf_key_converted = 'output_layer_parallelism' [/STATE] [STATE] conf_key_converted = 'scaled_upper_triang_masked_softmax_fusion' [/STATE] [STATE] conf_key_converted = 'bias_gelu_fusion' [/STATE] [STATE] conf_key_converted = 'rope_fusion' [/STATE] [STATE] conf_key_converted = 'init_method' [/STATE] [STATE] conf_key_converted = 'output_layer_init_method' [/STATE] [STATE] conf_key_converted = 'optimizer' [/STATE] [STATE] conf_key_converted = 'min_lr' [/STATE] [STATE] conf_key_converted = 'zero_optimization' [/STATE] [STATE] conf_key_converted = 'train_micro_batch_size_per_gpu' [/STATE]\n \"-\", \"_\"\n ) # TODO remove replace and update configuration files?\n config[conf_key_converted] = conf_value # [STATE] config = {'pipe_parallel_size': 1} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm'} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary'} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column'} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init'} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init'} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init', 'optimizer': {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init', 'optimizer': {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}, 'min_lr': 6e-05} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init', 'optimizer': {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}, 'min_lr': 6e-05, 'zero_optimization': {'stage': 1, 'allgather_partitions': True, 'allgather_bucket_size': 500000000, 'overlap_comm': True, 'reduce_scatter': True, 'reduce_bucket_size': 500000000, 'contiguous_gradients': True}} [/STATE] [STATE] config = {'pipe_parallel_size': 1, 'model_parallel_size': 1, 'num_layers': 12, 'hidden_size': 768, 'num_attention_heads': 12, 'seq_length': 2048, 'max_position_embeddings': 2048, 'norm': 'layernorm', 'pos_emb': 'rotary', 'no_weight_tying': True, 'gpt_j_residual': False, 'output_layer_parallelism': 'column', 'scaled_upper_triang_masked_softmax_fusion': False, 'bias_gelu_fusion': False, 'rope_fusion': False, 'init_method': 'small_init', 'output_layer_init_method': 'wang_init', 'optimizer': {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}}, 'min_lr': 6e-05, 'zero_optimization': {'stage': 1, 'allgather_partitions': True, 'allgather_bucket_size': 500000000, 'overlap_comm': True, 'reduce_scatter': True, 'reduce_bucket_size': 500000000, 'contiguous_gradients': True}, 'train_micro_batch_size_per_gpu': 4} [/STATE]\n\n # validate that neox args has the same value as specified in the config (if specified in the config)\n for k, v in config.items(): # [STATE] k = 'pipe_parallel_size' [/STATE] [STATE] v = 1 [/STATE] [STATE] k = 'model_parallel_size' [/STATE] [STATE] k = 'num_layers' [/STATE] [STATE] v = 12 [/STATE] [STATE] k = 'hidden_size' [/STATE] [STATE] v = 768 [/STATE] [STATE] k = 'num_attention_heads' [/STATE] [STATE] k = 'seq_length' [/STATE] [STATE] v = 2048 [/STATE] [STATE] k = 'max_position_embeddings' [/STATE] [STATE] k = 'norm' [/STATE] [STATE] v = 'layernorm' [/STATE] [STATE] k = 'pos_emb' [/STATE] [STATE] v = 'rotary' [/STATE] [STATE] k = 'no_weight_tying' [/STATE] [STATE] v = True [/STATE] [STATE] k = 'gpt_j_residual' [/STATE] [STATE] v = False [/STATE] [STATE] k = 'output_layer_parallelism' [/STATE] [STATE] v = 'column' [/STATE]\n neox_args_value = getattr(args_loaded, k) # [STATE] neox_args_value = 1 [/STATE] [STATE] neox_args_value = 12 [/STATE] [STATE] neox_args_value = 768 [/STATE] [STATE] neox_args_value = 2048 [/STATE] [STATE] neox_args_value = 'layernorm' [/STATE] [STATE] neox_args_value = 'rotary' [/STATE] [STATE] neox_args_value = True [/STATE] [STATE] neox_args_value = False [/STATE] [STATE] neox_args_value = 'column' [/STATE] [STATE] neox_args_value = 'small_init' [/STATE] [STATE] neox_args_value = 'wang_init' [/STATE] [STATE] neox_args_value = {'type': 'Adam', 'params': {'lr': 0.0006, 'betas': [0.9, 0.95], 'eps': 1e-08}} [/STATE] [STATE] neox_args_value = 6e-05 [/STATE] [STATE] neox_args_value = {'stage': 1, 'allgather_partitions': True, 'allgather_bucket_size': 500000000, 'overlap_comm': True, 'reduce_scatter': True, 'reduce_bucket_size': 500000000, 'contiguous_gradients': True} [/STATE] [STATE] neox_args_value = 4 [/STATE] [STATE] neox_args_value = 'mmap' [/STATE] [STATE] neox_args_value = 1.0 [/STATE] [STATE] neox_args_value = 0.1 [/STATE] [STATE] neox_args_value = 0.0 [/STATE] [STATE] neox_args_value = {'enabled': True, 'loss_scale': 0, 'loss_scale_window': 1000, 'hysteresis': 2, 'min_loss_scale': 1} [/STATE] [STATE] neox_args_value = 320000 [/STATE]\n assert v == neox_args_value, ( # [STATE] @py_assert1 = None [/STATE]\n \"loaded neox args value \"\n + str(k)\n + \" == \"\n + str(neox_args_value)\n + \" different from config file \"\n + str(v)\n )\n\nrun_neox_args_load_test(['125M.yml', 'local_setup.yml', 'cpu_mock_config.yml'])", "loop_code": "1: def run_neox_args_load_test(yaml_files):\n2: from megatron.neox_arguments import NeoXArgs\n3:\n4: yaml_list = get_configs_with_path(yaml_files)\n5: args_loaded = NeoXArgs.from_ymls(yaml_list)\n6: assert isinstance(args_loaded, NeoXArgs)\n7:\n8: # initialize an empty config dictionary to be filled by yamls\n9: config = dict()\n10:\n11: # iterate of all to be loaded yaml files\n12: for conf_file_name in yaml_list:\n13:\n14: # load file\n15: with open(conf_file_name) as conf_file:\n16: conf = yaml.load(conf_file, Loader=yaml.FullLoader)\n17:\n18: # check for key duplicates and load values\n19: for conf_key, conf_value in conf.items():\n20: if conf_key in config:\n21: raise ValueError(\n22: f\"Conf file {conf_file_name} has the following duplicate keys with previously loaded file: {conf_key}\"\n23: )\n24:\n25: conf_key_converted = conf_key.replace(\n26: \"-\", \"_\"\n27: ) # TODO remove replace and update configuration files?\n28: config[conf_key_converted] = conf_value\n29:\n30: # validate that neox args has the same value as specified in the config (if specified in the config)\n31: for k, v in config.items():\n32: neox_args_value = getattr(args_loaded, k)\n33: assert v == neox_args_value, (\n34: \"loaded neox args value \"\n35: + str(k)\n36: + \" == \"\n37: + str(neox_args_value)\n38: + \" different from config file \"\n39: + str(v)\n40: )\n41:\n42: run_neox_args_load_test(['125M.yml', 'local_setup.yml', 'cpu_mock_config.yml'])", "question": "What is the value of 'k' in line 31 after executing 'run_neox_args_load_test(['125M.yml', 'local_setup.yml', 'cpu_mock_config.yml'])'?", "answer": "'num_attention_heads'", "variable_assignment": "k = 'num_attention_heads'", "loop_range": [12, 28], "post_loop_line": 31} {"idx": 22, "scratchpad_format": "def main(input_args=None):\n args = get_args(input_args) # [STATE] args = Namespace(input='./tests/data/enwik8_first100.txt', jsonl_keys=['text'], num_docs=None, tokenizer_type='HFGPT2Tokenizer', vocab_file='gpt2', merge_file='./data/gpt2-merges.txt', append_eod=True, ftfy=False, output_prefix='./tests/data/enwik8_first100', dataset_impl='mmap', workers=1, log_interval=100, keep_empty=False, rank=0, make_vocab_size_divisible_by=128, model_parallel_size=1) [/STATE]\n encoder = Encoder(args) # [STATE] encoder = {args=Namespace(input='./tests/data/enwik8_first100.txt', jsonl_keys=['text'], num_docs=None, tokenizer_type='HFGPT2Tokenizer', vocab_file='gpt2', merge_file='./data/gpt2-merges.txt', append_eod=True, ftfy=False, output_prefix='./tests/data/enwik8_first100', dataset_impl='mmap', workers=1, log_interval=100, keep_empty=False, rank=0, make_vocab_size_divisible_by=128, model_parallel_size=1)} [/STATE]\n tokenizer = build_tokenizer(args) # [STATE] tokenizer = {name='HFGPT2TokenizerFast', tokenizer=GPT2TokenizerFast(name_or_path='gpt2', vocab_size=50257, model_max_length=1024, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'bos_token': '<|endoftext|>', 'eos_token': '<|endoftext|>', 'unk_token': '<|endoftext|>', 'pad_token': '<|padding|>'}, clean_up_tokenization_spaces=True), added_tokens_decoder={\t50256: AddedToken(\"<|endoftext|>\", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),\t50257: AddedToken(\"<|padding|>\", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),}, eod_id=50256, pad_id=50257} [/STATE] # [STATE] args = Namespace(input='./tests/data/enwik8_first100.txt', jsonl_keys=['text'], num_docs=None, tokenizer_type='HFGPT2Tokenizer', vocab_file='gpt2', merge_file='./data/gpt2-merges.txt', append_eod=True, ftfy=False, output_prefix='./tests/data/enwik8_first100', dataset_impl='mmap', workers=1, log_interval=100, keep_empty=False, rank=0, make_vocab_size_divisible_by=128, model_parallel_size=1, padded_vocab_size=50304) [/STATE] # [STATE] encoder = {args=Namespace(input='./tests/data/enwik8_first100.txt', jsonl_keys=['text'], num_docs=None, tokenizer_type='HFGPT2Tokenizer', vocab_file='gpt2', merge_file='./data/gpt2-merges.txt', append_eod=True, ftfy=False, output_prefix='./tests/data/enwik8_first100', dataset_impl='mmap', workers=1, log_interval=100, keep_empty=False, rank=0, make_vocab_size_divisible_by=128, model_parallel_size=1, padded_vocab_size=50304)} [/STATE]\n print(f\"Vocab size: {tokenizer.vocab_size}\")\n print(f\"Output prefix: {args.output_prefix}\")\n\n # build a semaphore object to stop `yield_from_files` from getting ahead of encoder.encode and\n # hence building up memory\n semaphore = Semaphore(10000 + args.workers) # [STATE] semaphore = {_cond=, 0)>, _value=10001} [/STATE]\n\n # use multiprocessing to iterate over input documents\n fin = yield_from_files(args.input.split(\",\"), semaphore) # [STATE] fin = [/STATE]\n\n if args.workers > 1:\n pool = multiprocessing.Pool(args.workers, initializer=encoder.initializer)\n encoded_docs = pool.imap(encoder.encode, fin, chunksize=25)\n else:\n encoder.initializer()\n encoded_docs = (encoder.encode(doc) for doc in fin) # [STATE] encoded_docs = . at 0x7f1a97c25270> [/STATE]\n\n # make a dataset builder for each key in args.jsonl_keys\n # each key will output to a different file beginning with args.output_prefix\n output_bin_files = {} # [STATE] output_bin_files = {} [/STATE]\n output_idx_files = {} # [STATE] output_idx_files = {} [/STATE]\n builders = {} # [STATE] builders = {} [/STATE]\n for key in args.jsonl_keys: # [STATE] key = 'text' [/STATE]\n output_bin_files[key] = \"{}_{}_{}.bin\".format( # [STATE] output_bin_files = {'text': './tests/data/enwik8_first100_text_document.bin'} [/STATE]\n args.output_prefix, key, \"document\"\n )\n output_idx_files[key] = \"{}_{}_{}.idx\".format( # [STATE] output_idx_files = {'text': './tests/data/enwik8_first100_text_document.idx'} [/STATE]\n args.output_prefix, key, \"document\"\n )\n builders[key] = indexed_dataset.make_builder( # [STATE] builders = {'text': } [/STATE]\n output_bin_files[key],\n impl=args.dataset_impl,\n vocab_size=tokenizer.vocab_size,\n )\n\n # actually do tokenization\n proc_start = time.time() # [STATE] proc_start = 1712171758.7156355 [/STATE]\n total_bytes_processed = 0 # [STATE] total_bytes_processed = 0 [/STATE]\n pbar = tqdm.tqdm() # [STATE] pbar = {iterable=None, desc='', total=None, leave=True, fp=, ncols=None, nrows=None, mininterval=0.1, maxinterval=10.0, miniters=0, dynamic_miniters=True, ascii=True, disable=False, unit='it', unit_scale=False, unit_divisor=1000, initial=0, lock_args=None, delay=0.0, gui=False, dynamic_ncols=False, smoothing=0.3, _ema_dn=, _ema_dt=, _ema_miniters=, bar_format=None, postfix=None, colour=None, _time=, last_print_n=0, n=0, pos=0, last_print_t=1712171758.7435398, start_t=1712171758.7435398} [/STATE]\n for i, (doc, bytes_processed) in enumerate(encoded_docs, start=1): # [STATE] i = 1 [/STATE] [STATE] doc = {'text': [[27, 11431, 15466, 35555, 5907, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 30487, 35555, 5907, 25, 87, 13396, 2625, 4023, 1378, 2503, 13, 86, 18, 13, 2398, 14, 14585, 14, 55, 5805, 27054, 2611, 12, 39098, 1, 2124, 13396, 25, 15952, 2611, 14749, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 14, 2638, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 13, 87, 21282, 1, 2196, 2625, 15, 13, 18, 1, 35555, 25, 17204, 2625, 268, 5320, 198, 220, 1279, 15654, 10951, 29, 198, 220, 220, 220, 1279, 48937, 12453, 29, 48845, 3556, 48937, 12453, 29, 198, 220, 220, 220, 1279, 8692, 29, 4023, 1378, 268, 13, 31266, 13, 2398, 14, 15466, 14, 13383, 62, 9876, 3556, 8692, 29, 198, 220, 220, 220, 1279, 8612, 1352, 29, 13152, 32603, 352, 13, 21, 26591, 3556, 8612, 1352, 29, 198, 220, 220, 220, 1279, 7442, 29, 11085, 12, 9291, 3556, 7442, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 43076, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 17, 5320, 13152, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 16, 5320, 13409, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 15, 1, 11037, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 16, 5320, 25685, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 17, 5320, 12982, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 18, 5320, 12982, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 19, 5320, 48845, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 20, 5320, 48845, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 21, 5320, 5159, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 22, 5320, 5159, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 23, 5320, 13152, 32603, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 24, 5320, 13152, 32603, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 940, 5320, 30800, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1157, 5320, 30800, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1065, 5320, 22087, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1485, 5320, 22087, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1415, 5320, 27313, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1314, 5320, 27313, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 3064, 5320, 13924, 282, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 8784, 5320, 13924, 282, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 7359, 14933, 43076, 29, 198, 220, 7359, 15654, 10951, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 32, 64, 32, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 16, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 34256, 2079, 27936, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 1065, 12, 1983, 51, 1507, 25, 3510, 25, 2857, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 49044, 4164, 7084, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 21, 23726, 1485, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 29697, 11907, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178...0, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3388, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1485, 25, 1485, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 1090, 62, 312, 28, 20, 25, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 2348, 1362, 544, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 7437, 16305, 12162, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 21, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3865, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1415, 25, 1558, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 284, 1090, 62, 312, 28, 21, 220, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 7437, 43663, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 4677, 18511, 40226, 873, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 23, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16942, 12, 2999, 12, 1495, 51, 1314, 25, 3559, 25, 1157, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 541, 29, 3103, 9641, 4226, 3556, 541, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 38062, 515, 11315, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 4677, 18511, 14458, 11907, 198, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 15457, 856, 5377, 48074, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 940, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 2231, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16088, 12, 3023, 12, 1495, 51, 1828, 25, 1507, 25, 2548, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 32, 907, 1795, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 2425, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 22743, 278, 18941, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 15457, 856, 62, 785, 48074, 11907, 3556, 5239, 29, 198, 50256]]} [/STATE] [STATE] bytes_processed = 3355 [/STATE] [STATE] semaphore = {_cond=, 0)>, _value=9999} [/STATE]\n total_bytes_processed += bytes_processed # [STATE] total_bytes_processed = 3355 [/STATE]\n\n # release semaphore so `yield_from_files` can add another file to the buffer\n semaphore.release() # [STATE] semaphore = {_cond=, 0)>, _value=10000} [/STATE]\n\n # add each tokenized document / sentence\n for key, sentences in doc.items(): # [STATE] sentences = [[27, 11431, 15466, 35555, 5907, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 30487, 35555, 5907, 25, 87, 13396, 2625, 4023, 1378, 2503, 13, 86, 18, 13, 2398, 14, 14585, 14, 55, 5805, 27054, 2611, 12, 39098, 1, 2124, 13396, 25, 15952, 2611, 14749, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 14, 2638, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 13, 87, 21282, 1, 2196, 2625, 15, 13, 18, 1, 35555, 25, 17204, 2625, 268, 5320, 198, 220, 1279, 15654, 10951, 29, 198, 220, 220, 220, 1279, 48937, 12453, 29, 48845, 3556, 48937, 12453, 29, 198, 220, 220, 220, 1279, 8692, 29, 4023, 1378, 268, 13, 31266, 13, 2398, 14, 15466, 14, 13383, 62, 9876, 3556, 8692, 29, 198, 220, 220, 220, 1279, 8612, 1352, 29, 13152, 32603, 352, 13, 21, 26591, 3556, 8612, 1352, 29, 198, 220, 220, 220, 1279, 7442, 29, 11085, 12, 9291, 3556, 7442, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 43076, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 17, 5320, 13152, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 16, 5320, 13409, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 15, 1, 11037, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 16, 5320, 25685, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 17, 5320, 12982, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 18, 5320, 12982, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 19, 5320, 48845, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 20, 5320, 48845, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 21, 5320, 5159, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 22, 5320, 5159, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 23, 5320, 13152, 32603, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 24, 5320, 13152, 32603, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 940, 5320, 30800, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1157, 5320, 30800, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1065, 5320, 22087, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1485, 5320, 22087, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1415, 5320, 27313, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1314, 5320, 27313, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 3064, 5320, 13924, 282, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 8784, 5320, 13924, 282, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 7359, 14933, 43076, 29, 198, 220, 7359, 15654, 10951, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 32, 64, 32, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 16, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 34256, 2079, 27936, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 1065, 12, 1983, 51, 1507, 25, 3510, 25, 2857, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 49044, 4164, 7084, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 21, 23726, 1485, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 29697, 11907, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198...20, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3388, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1485, 25, 1485, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 1090, 62, 312, 28, 20, 25, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 2348, 1362, 544, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 7437, 16305, 12162, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 21, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3865, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1415, 25, 1558, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 284, 1090, 62, 312, 28, 21, 220, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 7437, 43663, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 4677, 18511, 40226, 873, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 23, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16942, 12, 2999, 12, 1495, 51, 1314, 25, 3559, 25, 1157, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 541, 29, 3103, 9641, 4226, 3556, 541, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 38062, 515, 11315, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 4677, 18511, 14458, 11907, 198, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 15457, 856, 5377, 48074, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 940, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 2231, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16088, 12, 3023, 12, 1495, 51, 1828, 25, 1507, 25, 2548, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 32, 907, 1795, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 2425, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 22743, 278, 18941, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 15457, 856, 62, 785, 48074, 11907, 3556, 5239, 29, 198, 50256]] [/STATE]\n for sentence in sentences: # [STATE] sentence = [27, 11431, 15466, 35555, 5907, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 30487, 35555, 5907, 25, 87, 13396, 2625, 4023, 1378, 2503, 13, 86, 18, 13, 2398, 14, 14585, 14, 55, 5805, 27054, 2611, 12, 39098, 1, 2124, 13396, 25, 15952, 2611, 14749, 2625, 4023, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 14, 2638, 1378, 2503, 13, 11431, 15466, 13, 2398, 14, 19875, 14, 39344, 12, 15, 13, 18, 13, 87, 21282, 1, 2196, 2625, 15, 13, 18, 1, 35555, 25, 17204, 2625, 268, 5320, 198, 220, 1279, 15654, 10951, 29, 198, 220, 220, 220, 1279, 48937, 12453, 29, 48845, 3556, 48937, 12453, 29, 198, 220, 220, 220, 1279, 8692, 29, 4023, 1378, 268, 13, 31266, 13, 2398, 14, 15466, 14, 13383, 62, 9876, 3556, 8692, 29, 198, 220, 220, 220, 1279, 8612, 1352, 29, 13152, 32603, 352, 13, 21, 26591, 3556, 8612, 1352, 29, 198, 220, 220, 220, 1279, 7442, 29, 11085, 12, 9291, 3556, 7442, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 43076, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 17, 5320, 13152, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 12, 16, 5320, 13409, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 15, 1, 11037, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 16, 5320, 25685, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 17, 5320, 12982, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 18, 5320, 12982, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 19, 5320, 48845, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 20, 5320, 48845, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 21, 5320, 5159, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 22, 5320, 5159, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 23, 5320, 13152, 32603, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 24, 5320, 13152, 32603, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 940, 5320, 30800, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1157, 5320, 30800, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1065, 5320, 22087, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1485, 5320, 22087, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1415, 5320, 27313, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 1314, 5320, 27313, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 3064, 5320, 13924, 282, 3556, 14933, 10223, 29, 198, 220, 220, 220, 220, 220, 1279, 14933, 10223, 1994, 2625, 8784, 5320, 13924, 282, 1561, 3556, 14933, 10223, 29, 198, 220, 220, 220, 7359, 14933, 43076, 29, 198, 220, 7359, 15654, 10951, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 32, 64, 32, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 16, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 34256, 2079, 27936, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 1065, 12, 1983, 51, 1507, 25, 3510, 25, 2857, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 49044, 4164, 7084, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 21, 23726, 1485, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 29697, 11907, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198,...220, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3388, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1485, 25, 1485, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 1090, 62, 312, 28, 20, 25, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 2348, 1362, 544, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 7437, 16305, 12162, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 21, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 1507, 3312, 2718, 3865, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 14315, 12, 2998, 12, 3070, 51, 1157, 25, 1415, 25, 1558, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 23579, 84, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 1795, 1959, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 26872, 284, 1090, 62, 312, 28, 21, 220, 22935, 49, 422, 43281, 20448, 11709, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 7437, 43663, 11907, 27007, 49, 422, 43281, 20448, 11709, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 4677, 18511, 40226, 873, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 23, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16942, 12, 2999, 12, 1495, 51, 1314, 25, 3559, 25, 1157, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 541, 29, 3103, 9641, 4226, 3556, 541, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 38062, 515, 11315, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 4677, 18511, 14458, 11907, 198, 3556, 5239, 29, 198, 220, 220, 220, 7359, 260, 10178, 29, 198, 220, 7359, 7700, 29, 198, 220, 1279, 7700, 29, 198, 220, 220, 220, 1279, 7839, 29, 15457, 856, 5377, 48074, 3556, 7839, 29, 198, 220, 220, 220, 1279, 312, 29, 940, 3556, 312, 29, 198, 220, 220, 220, 1279, 260, 10178, 29, 198, 220, 220, 220, 220, 220, 1279, 312, 29, 21273, 42520, 2231, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 1279, 16514, 27823, 29, 16088, 12, 3023, 12, 1495, 51, 1828, 25, 1507, 25, 2548, 57, 3556, 16514, 27823, 29, 198, 220, 220, 220, 220, 220, 1279, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 29460, 29, 32, 907, 1795, 3556, 29460, 29, 198, 220, 220, 220, 220, 220, 220, 220, 1279, 312, 29, 2425, 3559, 3556, 312, 29, 198, 220, 220, 220, 220, 220, 7359, 3642, 2455, 273, 29, 198, 220, 220, 220, 220, 220, 1279, 1084, 273, 11037, 198, 220, 220, 220, 220, 220, 1279, 23893, 29, 22743, 278, 18941, 3556, 23893, 29, 198, 220, 220, 220, 220, 220, 1279, 5239, 35555, 25, 13200, 2625, 18302, 3760, 5320, 2, 22083, 40, 23988, 16410, 15457, 856, 62, 785, 48074, 11907, 3556, 5239, 29, 198, 50256] [/STATE]\n builders[key].add_item(np.array(sentence, dtype=builders[key].dtype))\n # separate with eos token\n builders[key].end_document()\n\n # log progress\n if i % args.log_interval == 0:\n current = time.time()\n elapsed = current - proc_start\n mbs = total_bytes_processed / elapsed / 1024 / 1024\n pbar.set_description(\n f\"Processed {i}{'' if args.num_docs is None else '/' + str(args.num_docs)} documents ({i / elapsed :.2f} docs/s, {mbs:.2f} MB/s).\"\n )\n if i != 0:\n pbar.update(args.log_interval)\n\n # save output file\n for key in args.jsonl_keys:\n builders[key].finalize(output_idx_files[key])\n\nmain(['--input', './tests/data/enwik8_first100.txt', '--output-prefix', './tests/data/enwik8_first100', '--vocab', 'gpt2', '--tokenizer-type', 'HFGPT2Tokenizer', '--merge-file', './data/gpt2-merges.txt', '--append-eod'])", "loop_code": "1: def main(input_args=None):\n2: args = get_args(input_args)\n3: encoder = Encoder(args)\n4: tokenizer = build_tokenizer(args)\n5: print(f\"Vocab size: {tokenizer.vocab_size}\")\n6: print(f\"Output prefix: {args.output_prefix}\")\n7:\n8: # build a semaphore object to stop `yield_from_files` from getting ahead of encoder.encode and\n9: # hence building up memory\n10: semaphore = Semaphore(10000 + args.workers)\n11:\n12: # use multiprocessing to iterate over input documents\n13: fin = yield_from_files(args.input.split(\",\"), semaphore)\n14:\n15: if args.workers > 1:\n16: pool = multiprocessing.Pool(args.workers, initializer=encoder.initializer)\n17: encoded_docs = pool.imap(encoder.encode, fin, chunksize=25)\n18: else:\n19: encoder.initializer()\n20: encoded_docs = (encoder.encode(doc) for doc in fin)\n21:\n22: # make a dataset builder for each key in args.jsonl_keys\n23: # each key will output to a different file beginning with args.output_prefix\n24: output_bin_files = {}\n25: output_idx_files = {}\n26: builders = {}\n27: for key in args.jsonl_keys:\n28: output_bin_files[key] = \"{}_{}_{}.bin\".format(\n29: args.output_prefix, key, \"document\"\n30: )\n31: output_idx_files[key] = \"{}_{}_{}.idx\".format(\n32: args.output_prefix, key, \"document\"\n33: )\n34: builders[key] = indexed_dataset.make_builder(\n35: output_bin_files[key],\n36: impl=args.dataset_impl,\n37: vocab_size=tokenizer.vocab_size,\n38: )\n39:\n40: # actually do tokenization\n41: proc_start = time.time()\n42: total_bytes_processed = 0\n43: pbar = tqdm.tqdm()\n44: for i, (doc, bytes_processed) in enumerate(encoded_docs, start=1):\n45: total_bytes_processed += bytes_processed\n46:\n47: # release semaphore so `yield_from_files` can add another file to the buffer\n48: semaphore.release()\n49:\n50: # add each tokenized document / sentence\n51: for key, sentences in doc.items():\n52: for sentence in sentences:\n53: builders[key].add_item(np.array(sentence, dtype=builders[key].dtype))\n54: # separate with eos token\n55: builders[key].end_document()\n56:\n57: # log progress\n58: if i % args.log_interval == 0:\n59: current = time.time()\n60: elapsed = current - proc_start\n61: mbs = total_bytes_processed / elapsed / 1024 / 1024\n62: pbar.set_description(\n63: f\"Processed {i}{'' if args.num_docs is None else '/' + str(args.num_docs)} documents ({i / elapsed :.2f} docs/s, {mbs:.2f} MB/s).\"\n64: )\n65: if i != 0:\n66: pbar.update(args.log_interval)\n67:\n68: # save output file\n69: for key in args.jsonl_keys:\n70: builders[key].finalize(output_idx_files[key])\n71:\n72: main(['--input', './tests/data/enwik8_first100.txt', '--output-prefix', './tests/data/enwik8_first100', '--vocab', 'gpt2', '--tokenizer-type', 'HFGPT2Tokenizer', '--merge-file', './data/gpt2-merges.txt', '--append-eod'])", "question": "What is the value of 'proc_start' in line 41 after executing 'main(['--input', './tests/data/enwik8_first100.txt', '--output-prefix', './tests/data/enwik8_first100', '--vocab', 'gpt2', '--tokenizer-type', 'HFGPT2Tokenizer', '--merge-file', './data/gpt2-merges.txt', '--append-eod'])'?", "answer": "1712171758.7156355", "variable_assignment": "proc_start = 1712171758.7156355", "loop_range": [27, 38], "post_loop_line": 41} {"idx": 23, "scratchpad_format": "def get_article_detail(text, del_qqmusic=True, del_voice=True):\n \"\"\"\u6839\u636e\u5fae\u4fe1\u6587\u7ae0\u7684\u4e34\u65f6\u94fe\u63a5\u83b7\u53d6\u660e\u7ec6\n\n 1. \u83b7\u53d6\u6587\u672c\u4e2d\u6240\u6709\u7684\u56fe\u7247\u94fe\u63a5\u5217\u8868\n 2. \u83b7\u53d6\u5fae\u4fe1\u6587\u7ae0\u7684html\u5185\u5bb9\u9875\u9762(\u53bb\u9664\u6807\u9898\u7b49\u4fe1\u606f)\n\n Parameters\n ----------\n text : str or unicode\n \u4e00\u7bc7\u5fae\u4fe1\u6587\u7ae0\u7684\u6587\u672c\n del_qqmusic: bool\n \u5220\u9664\u6587\u7ae0\u4e2d\u7684qq\u97f3\u4e50\n del_voice: bool\n \u5220\u9664\u6587\u7ae0\u4e2d\u7684\u8bed\u97f3\u5185\u5bb9\n\n Returns\n -------\n dict\n {\n 'content_html': str # \u5fae\u4fe1\u6587\u672c\u5185\u5bb9\n 'content_img_list': list[img_url1, img_url2, ...] # \u5fae\u4fe1\u6587\u672c\u4e2d\u56fe\u7247\u5217\u8868\n\n }\n \"\"\"\n # 1. \u83b7\u53d6\u5fae\u4fe1\u6587\u672ccontent\n html_obj = BeautifulSoup(text, \"lxml\") # [STATE] html_obj = [/STATE]\n content_text = html_obj.find('div', {'class': 'rich_media_content', 'id': 'js_content'}) # [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b


\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE]\n\n # 2. \u5220\u9664\u90e8\u5206\u6807\u7b7e\n if del_qqmusic:\n qqmusic = content_text.find_all('qqmusic') or [] # [STATE] qqmusic = [] [/STATE]\n for music in qqmusic: # [STATE] music = [/STATE]\n music.parent.decompose() # [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] # [STATE] qqmusic = REPR FAILED [/STATE] # [STATE] music = REPR FAILED [/STATE]\n\n if del_voice:\n # voice\u662f\u4e00\u4e2ap\u6807\u7b7e\u4e0b\u7684mpvoice\u6807\u7b7e\u4ee5\u53caclass\u4e3a'js_audio_frame db'\u7684span\u6784\u6210\uff0c\u6240\u4ee5\u5c06\u7236\u6807\u7b7e\u5220\u9664\n voices = content_text.find_all('mpvoice') or [] # [STATE] voices = [] [/STATE]\n for voice in voices:\n voice.parent.decompose()\n\n # 3. \u83b7\u53d6\u6240\u6709\u7684\u56fe\u7247 [img\u6807\u7b7e\uff0c\u548cstyle\u4e2d\u7684background-image]\n all_img_set = set() # [STATE] all_img_set = set() [/STATE]\n all_img_element = content_text.find_all('img') or [] # [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE]\n for ele in all_img_element: # [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE] [STATE] ele = [/STATE]\n # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n img_url = format_image_url(ele.attrs['data-src']) # [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErux30g1cwicx2awgxGUrVAq3G6kACAWqdoAZ1jdjuLv7ShVjp9fjtKkcQ/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruMagzpWJa3IowapejQRxeaN9xNG1ond1XQ7Kd4TUtnSCqTMPJm50UWQ/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_jpg/oq1PymRl9D7wicq1tSoqEUMOFsicSz0VMHQGKRJDOVGNqve308J4BjpiaqhdcJaFgicVsdn88v5icRLPWRyE4Um2M5g/640?wx_fmt=jpeg' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruGeGwW9Io6ibmFOteW04ibmg5HT8DKfEvfoojVleRiaibgON6Fwr6Hhanwg/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruPfXZic5rn0ddft1UrbQdz1PvEmMhoQ5cw87H7gL0PImMlF4UB5wpkSg/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEru7Y9cXa6t7b4sKlcURer8XpRkP84hURFRWJkSibUlDySMUdyPA8lxmSw/640?wx_fmt=png' [/STATE] [STATE] img_url = 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruxgJMkE11iao5lr8OibR9f9yqIrHx2cxUCu65pzIZP3auOicenn1dDpvkA/640?wx_fmt=png' [/STATE]\n del ele.attrs['data-src'] # [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE]\n\n ele.attrs['src'] = img_url # [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE] [STATE] ele = [/STATE] [STATE] all_img_element = [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] [/STATE]\n\n if not img_url.startswith('http'):\n raise WechatSogouException('img_url [{}] \u4e0d\u5408\u6cd5'.format(img_url))\n all_img_set.add(img_url) # [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640'} [/STATE] [STATE] all_img_set 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'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruMagzpWJa3IowapejQRxeaN9xNG1ond1XQ7Kd4TUtnSCqTMPJm50UWQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruGeGwW9Io6ibmFOteW04ibmg5HT8DKfEvfoojVleRiaibgON6Fwr6Hhanwg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEru7Y9cXa6t7b4sKlcURer8XpRkP84hURFRWJkSibUlDySMUdyPA8lxmSw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/oq1PymRl9D7wicq1tSoqEUMOFsicSz0VMHQGKRJDOVGNqve308J4BjpiaqhdcJaFgicVsdn88v5icRLPWRyE4Um2M5g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruPfXZic5rn0ddft1UrbQdz1PvEmMhoQ5cw87H7gL0PImMlF4UB5wpkSg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErux30g1cwicx2awgxGUrVAq3G6kACAWqdoAZ1jdjuLv7ShVjp9fjtKkcQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png'} [/STATE] [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruMagzpWJa3IowapejQRxeaN9xNG1ond1XQ7Kd4TUtnSCqTMPJm50UWQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruGeGwW9Io6ibmFOteW04ibmg5HT8DKfEvfoojVleRiaibgON6Fwr6Hhanwg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEru7Y9cXa6t7b4sKlcURer8XpRkP84hURFRWJkSibUlDySMUdyPA8lxmSw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/oq1PymRl9D7wicq1tSoqEUMOFsicSz0VMHQGKRJDOVGNqve308J4BjpiaqhdcJaFgicVsdn88v5icRLPWRyE4Um2M5g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruPfXZic5rn0ddft1UrbQdz1PvEmMhoQ5cw87H7gL0PImMlF4UB5wpkSg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErux30g1cwicx2awgxGUrVAq3G6kACAWqdoAZ1jdjuLv7ShVjp9fjtKkcQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruxgJMkE11iao5lr8OibR9f9yqIrHx2cxUCu65pzIZP3auOicenn1dDpvkA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png'} [/STATE]\n\n backgroud_image = content_text.find_all(style=re.compile(\"background-image\")) or [] # [STATE] backgroud_image = [
] [/STATE]\n for ele in backgroud_image: # [STATE] ele =
[/STATE]\n # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n if ele.attrs.get('data-src'):\n del ele.attrs['data-src']\n\n if ele.attrs.get('data-wxurl'):\n del ele.attrs['data-wxurl'] # [STATE] content_text =

\u00a0\u65e9\u4e0a\u597d~

\u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c

\u4e0d\u8d70\u51fa\u53bb\uff0c

\u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b



\u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~


[/STATE] # [STATE] ele =
[/STATE] # [STATE] backgroud_image = [
] [/STATE]\n img_url = re.findall(backgroud_image_p, str(ele)) # [STATE] img_url = ['https://mmbiz.qpic.cn/mmbiz_jpg/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRHGXoMtN8oReOYz7SkiaHJqjk7ACtFQfUOhQkibtofRZt463fujIwQcicg/640?wx_fmt=jpeg'] [/STATE]\n if not img_url:\n continue\n all_img_set.add(img_url[0]) # [STATE] all_img_set = {'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruNFHXlrc4bmxH3DWgqn0tvBSHUTg6fcF9DUGlDf2kJFmmHrAtvicha1A/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruMagzpWJa3IowapejQRxeaN9xNG1ond1XQ7Kd4TUtnSCqTMPJm50UWQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruGeGwW9Io6ibmFOteW04ibmg5HT8DKfEvfoojVleRiaibgON6Fwr6Hhanwg/640?wx_fmt=png', 'http://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiagSm5VtCHMcEYXtrmgBK4U7liaapv8Mhicwf05CWlM0JicxzBAs4QDQt2xOMVuL9Y4tEKSG1tSDVvOnA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRHGXoMtN8oReOYz7SkiaHJqjk7ACtFQfUOhQkibtofRZt463fujIwQcicg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruBcqVLOZsEGT1fRZvsRsmRqCl6eyLrYHR0kwovFhkjU8dSvhzs2mtRA/640?wx_fmt=png', 'http://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajJ1SEqcphq0AdJklqfSBSmfah3nFRxglymcibajPooleKzlV9qZZy5FcyOqDOuH5QibXVR0cuiahRkQ/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz/ianq03UUWGmK4x8wVTdM27HAUGhBg5y42uC4diafFxJ2oeg8gsqbRRfjOMibqibaUEg2AicYRX1YpE1ne58SMR2XGkQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEru7Y9cXa6t7b4sKlcURer8XpRkP84hURFRWJkSibUlDySMUdyPA8lxmSw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/oq1PymRl9D7wicq1tSoqEUMOFsicSz0VMHQGKRJDOVGNqve308J4BjpiaqhdcJaFgicVsdn88v5icRLPWRyE4Um2M5g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruPfXZic5rn0ddft1UrbQdz1PvEmMhoQ5cw87H7gL0PImMlF4UB5wpkSg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiajJ1SEqcphq0AdJklqfSBSmC42xAdtpV7C8YpDSZ6JXO52pg0m3cv5AfNpNeooyIsqQKS5D5lfTmQ/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErux30g1cwicx2awgxGUrVAq3G6kACAWqdoAZ1jdjuLv7ShVjp9fjtKkcQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruxgJMkE11iao5lr8OibR9f9yqIrHx2cxUCu65pzIZP3auOicenn1dDpvkA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwqLtGOkNR3jeI17pRBmuicnRJDNsjltcb7Y9rBOh7jxe0S3iadnGsnEXg/640?wx_fmt=jpeg'} [/STATE]\n\n # 4. \u5904\u7406iframe\n all_img_element = content_text.find_all('iframe') or [] # [STATE] all_img_element = [] [/STATE]\n for ele in all_img_element:\n # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n img_url = ele.attrs['data-src']\n del ele.attrs['data-src']\n ele.attrs['src'] = img_url\n\n # 5. \u8fd4\u56de\u6570\u636e\n all_img_list = list(all_img_set) # [STATE] all_img_list = ['https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRYoicViaW9XPCpzfumwpdbOg0icWwx9OGEjuOgF7OCxLYxf0ibXz3T5ogxQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulWic8GkI4jTUAOfJrme36PZwQ2dic784yPtYumdthOKGrLYHfemicV6Hw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruNFHXlrc4bmxH3DWgqn0tvBSHUTg6fcF9DUGlDf2kJFmmHrAtvicha1A/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruMagzpWJa3IowapejQRxeaN9xNG1ond1XQ7Kd4TUtnSCqTMPJm50UWQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruGeGwW9Io6ibmFOteW04ibmg5HT8DKfEvfoojVleRiaibgON6Fwr6Hhanwg/640?wx_fmt=png', 'http://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiagSm5VtCHMcEYXtrmgBK4U7liaapv8Mhicwf05CWlM0JicxzBAs4QDQt2xOMVuL9Y4tEKSG1tSDVvOnA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/Jyco923vDiahUG7Gqyp3hMzafzu1MqfvRHGXoMtN8oReOYz7SkiaHJqjk7ACtFQfUOhQkibtofRZt463fujIwQcicg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruBcqVLOZsEGT1fRZvsRsmRqCl6eyLrYHR0kwovFhkjU8dSvhzs2mtRA/640?wx_fmt=png', 'http://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajJ1SEqcphq0AdJklqfSBSmfah3nFRxglymcibajPooleKzlV9qZZy5FcyOqDOuH5QibXVR0cuiahRkQ/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErulge7eq0v065JzON3PwdUWSXMPh9PLNRRmI9l4t8g5m4HYvhLCM73kg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz/ianq03UUWGmK4x8wVTdM27HAUGhBg5y42uC4diafFxJ2oeg8gsqbRRfjOMibqibaUEg2AicYRX1YpE1ne58SMR2XGkQ/640?wx_fmt=gif', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEru7Y9cXa6t7b4sKlcURer8XpRkP84hURFRWJkSibUlDySMUdyPA8lxmSw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/oq1PymRl9D7wicq1tSoqEUMOFsicSz0VMHQGKRJDOVGNqve308J4BjpiaqhdcJaFgicVsdn88v5icRLPWRyE4Um2M5g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruPfXZic5rn0ddft1UrbQdz1PvEmMhoQ5cw87H7gL0PImMlF4UB5wpkSg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErumf6Uuyibn37TsUkRY4Ahzxib69WZN0UP5b9iblJx7baFzCVdv7iakEyqkw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_gif/Jyco923vDiajJ1SEqcphq0AdJklqfSBSmC42xAdtpV7C8YpDSZ6JXO52pg0m3cv5AfNpNeooyIsqQKS5D5lfTmQ/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErux30g1cwicx2awgxGUrVAq3G6kACAWqdoAZ1jdjuLv7ShVjp9fjtKkcQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwloSIbsVMqDDYSQyjZ7sPdAl17PBJptmWGKvPCO2z3p9DPp6HwBmpcg/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_jpg/xrFYciaHL08BQibj45TouE53ViauIKoykFLFe6qb4jYnHM9xxicibN1gFfFVMUfMicqeTF3SYz25IaSxgbDvXGEFxK0g/640?wx_fmt=jpeg', 'https://mmbiz.qpic.cn/mmbiz_gif/v4vz52CcB10icDUYXeCCiatGPFKaHaOBnWIARweIA8tLOrFS5N5BBByIwqO8yCVjuUzwYAa2HuxiabDzQHtYD61Bw/640?', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruxgJMkE11iao5lr8OibR9f9yqIrHx2cxUCu65pzIZP3auOicenn1dDpvkA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErutPdD6pGvqMWZXBvtDl6Q72CuTpRa5C2eOPVswhh7W6rDXic45pRicdkg/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgErucGICXziaPSicIltx8Of5CkDJjKy6dxiclrVvByiabLaO7p3uZibTNmfhTxw/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruJD3CIeXArI8asI4qxCoqYuNN7paYWa4XfP2JuD6SjuF6OqTwgIzt7g/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruaXSrvfWk7B0jvWEogxVf8WvriaPGZjFwxtKPaKrmUBkfYxgOAZfR4rQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruQDBRUibgY8e14K7eR4x6fxMibeQ2ibJzuFNujBpVGHlacOW3iajP6zvsAA/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_png/v4vz52CcB13K0y1mCNoDfAMJ4nqJkGapfrQJ4KiatPCu1xiaiaFGF3DNfvhUCYliaKV0UVm2LtDrYRxtFnQ3IvL5RA/640', 'https://mmbiz.qpic.cn/mmbiz_png/Jyco923vDiajsBt80vSPPsBtpefTAgEruXXUwTb1e7uoXOvTJSexke9YgfkicFyibTria7CDgfia8VBUj6Q2XQqVIDQ/640?wx_fmt=png', 'https://mmbiz.qpic.cn/mmbiz_jpg/azXQmS1HA7lxZkZaxyTQ8yqLM57WTkZwqLtGOkNR3jeI17pRBmuicnRJDNsjltcb7Y9rBOh7jxe0S3iadnGsnEXg/640?wx_fmt=jpeg'] [/STATE]\n content_html = content_text.prettify() # [STATE] content_html = '
\\n
\\n
\\n
\\n
\\n
\\n \\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n

\\n \\n

\\n
\\n
\\n

\\n \u65e9\u4e0a\u597d~\\n

\\n
\\n
\\n
\\n

\\n \\n \u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c\\n \\n

\\n

\\n \\n \u4e0d\u8d70\u51fa\u53bb\uff0c\\n \\n

\\n

\\n \\n \u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b\\n \\n

\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n

\\n
\\n

\\n
\\n
\\n
\\n
\\n

\\n
\\n
\\n
\\n

\\n
\\n

\\n
\\n \\n
\\n
\\n
\\n
\\n

\\n \\n \\n \u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~\\n \\n \\n

\\n

\\n
\\n

\\n
\\n
\\n
\\n
\\n
\\n

\\n \\n

\\n

\\n \\n

\\n
\\n
\\n

\\n \\n

\\n
\\n
\\n' [/STATE]\n # \u53bb\u9664div[id=js_content]\n content_html = re.findall(js_content, content_html)[0][0] # [STATE] content_html = '\\n
\\n
\\n
\\n
\\n
\\n \\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n

\\n \\n

\\n
\\n
\\n

\\n \u65e9\u4e0a\u597d~\\n

\\n
\\n
\\n
\\n

\\n \\n \u4e0d\u8981\u603b\u5446\u5728\u81ea\u5df1\u7684\u8212\u9002\u5708\u91cc\uff0c\\n \\n

\\n

\\n \\n \u4e0d\u8d70\u51fa\u53bb\uff0c\\n \\n

\\n

\\n \\n \u4f60\u5f88\u96be\u53d1\u73b0\u81ea\u5df1\u7684\u6f5c\u529b\\n \\n

\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n
\\n

\\n
\\n

\\n
\\n
\\n
\\n
\\n

\\n
\\n
\\n
\\n

\\n
\\n

\\n
\\n \\n
\\n
\\n
\\n
\\n

\\n \\n \\n \u6b22\u8fce\u5206\u4eab\u5230\u670b\u53cb\u5708~\\n \\n \\n

\\n

\\n
\\n

\\n
\\n
\\n
\\n
\\n
\\n

\\n \\n

\\n

\\n \\n

\\n
\\n
\\n

\\n \\n

\\n
\\n' [/STATE]\n return {\n 'content_html': content_html,\n 'content_img_list': all_img_list\n }\n\nget_article_detail('\\n\\n\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n \\n\\n \\n \\n \\n\\n\\n\\n\\n\\n', True, True)", "loop_code": "1: def get_article_detail(text, del_qqmusic=True, del_voice=True):\n2: \"\"\"\u6839\u636e\u5fae\u4fe1\u6587\u7ae0\u7684\u4e34\u65f6\u94fe\u63a5\u83b7\u53d6\u660e\u7ec6\n3:\n4: 1. \u83b7\u53d6\u6587\u672c\u4e2d\u6240\u6709\u7684\u56fe\u7247\u94fe\u63a5\u5217\u8868\n5: 2. \u83b7\u53d6\u5fae\u4fe1\u6587\u7ae0\u7684html\u5185\u5bb9\u9875\u9762(\u53bb\u9664\u6807\u9898\u7b49\u4fe1\u606f)\n6:\n7: Parameters\n8: ----------\n9: text : str or unicode\n10: \u4e00\u7bc7\u5fae\u4fe1\u6587\u7ae0\u7684\u6587\u672c\n11: del_qqmusic: bool\n12: \u5220\u9664\u6587\u7ae0\u4e2d\u7684qq\u97f3\u4e50\n13: del_voice: bool\n14: \u5220\u9664\u6587\u7ae0\u4e2d\u7684\u8bed\u97f3\u5185\u5bb9\n15:\n16: Returns\n17: -------\n18: dict\n19: {\n20: 'content_html': str # \u5fae\u4fe1\u6587\u672c\u5185\u5bb9\n21: 'content_img_list': list[img_url1, img_url2, ...] # \u5fae\u4fe1\u6587\u672c\u4e2d\u56fe\u7247\u5217\u8868\n22:\n23: }\n24: \"\"\"\n25: # 1. \u83b7\u53d6\u5fae\u4fe1\u6587\u672ccontent\n26: html_obj = BeautifulSoup(text, \"lxml\")\n27: content_text = html_obj.find('div', {'class': 'rich_media_content', 'id': 'js_content'})\n28:\n29: # 2. \u5220\u9664\u90e8\u5206\u6807\u7b7e\n30: if del_qqmusic:\n31: qqmusic = content_text.find_all('qqmusic') or []\n32: for music in qqmusic:\n33: music.parent.decompose()\n34:\n35: if del_voice:\n36: # voice\u662f\u4e00\u4e2ap\u6807\u7b7e\u4e0b\u7684mpvoice\u6807\u7b7e\u4ee5\u53caclass\u4e3a'js_audio_frame db'\u7684span\u6784\u6210\uff0c\u6240\u4ee5\u5c06\u7236\u6807\u7b7e\u5220\u9664\n37: voices = content_text.find_all('mpvoice') or []\n38: for voice in voices:\n39: voice.parent.decompose()\n40:\n41: # 3. \u83b7\u53d6\u6240\u6709\u7684\u56fe\u7247 [img\u6807\u7b7e\uff0c\u548cstyle\u4e2d\u7684background-image]\n42: all_img_set = set()\n43: all_img_element = content_text.find_all('img') or []\n44: for ele in all_img_element:\n45: # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n46: img_url = format_image_url(ele.attrs['data-src'])\n47: del ele.attrs['data-src']\n48:\n49: ele.attrs['src'] = img_url\n50:\n51: if not img_url.startswith('http'):\n52: raise WechatSogouException('img_url [{}] \u4e0d\u5408\u6cd5'.format(img_url))\n53: all_img_set.add(img_url)\n54:\n55: backgroud_image = content_text.find_all(style=re.compile(\"background-image\")) or []\n56: for ele in backgroud_image:\n57: # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n58: if ele.attrs.get('data-src'):\n59: del ele.attrs['data-src']\n60:\n61: if ele.attrs.get('data-wxurl'):\n62: del ele.attrs['data-wxurl']\n63: img_url = re.findall(backgroud_image_p, str(ele))\n64: if not img_url:\n65: continue\n66: all_img_set.add(img_url[0])\n67:\n68: # 4. \u5904\u7406iframe\n69: all_img_element = content_text.find_all('iframe') or []\n70: for ele in all_img_element:\n71: # \u5220\u9664\u90e8\u5206\u5c5e\u6027\n72: img_url = ele.attrs['data-src']\n73: del ele.attrs['data-src']\n74: ele.attrs['src'] = img_url\n75:\n76: # 5. \u8fd4\u56de\u6570\u636e\n77: all_img_list = list(all_img_set)\n78: content_html = content_text.prettify()\n79: # \u53bb\u9664div[id=js_content]\n80: content_html = re.findall(js_content, content_html)[0][0]\n81: return {\n82: 'content_html': content_html,\n83: 'content_img_list': all_img_list\n84: }\n85:\n86: get_article_detail('\\n\\n\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n \\n\\n \\n \\n \\n\\n\\n\\n\\n\\n', True, True)", "question": "What is the value of 'all_img_element' in line 69 after executing 'get_article_detail('\\n\\n\\n\\n \\n \\n \\n \\n \\n \\n\\n\\n \\n\\n \\n \\n \\n\\n\\n\\n\\n\\n', True, True)'?", "answer": "[]", "variable_assignment": "all_img_element = []", "loop_range": [56, 66], "post_loop_line": 69} {"idx": 24, "scratchpad_format": "def dump_from_base(args: list) -> None:\n \"\"\"\n Dump memory from a base address for a specific size to file\n\n :param args:\n :return:\n \"\"\"\n\n if len(clean_argument_flags(args)) < 3:\n click.secho('Usage: memory dump from_base ', bold=True)\n return\n\n # the destination file to write the dump to\n base_address = args[0] # [STATE] base_address = '0x00008000' [/STATE]\n memory_size = args[1] # [STATE] memory_size = '200' [/STATE]\n destination = args[2] # [STATE] destination = '/foo' [/STATE]\n\n # Check for file override\n if os.path.exists(destination):\n click.secho('Destination file {dest} already exists'.format(dest=destination), fg='yellow', bold=True)\n if not click.confirm('Override?'):\n return\n\n click.secho('Dumping {0} from {1} to {2}'.format(sizeof_fmt(int(memory_size)), base_address, destination),\n fg='green', dim=True)\n\n api = state_connection.get_api() # [STATE] api = [/STATE]\n\n # iirc, if you don't cast the return type to a bytearray it uses the sizeof(int) per cell, which is massive\n dump = bytearray() # [STATE] dump = bytearray(b'') [/STATE]\n chunks = _get_chunks(int(base_address, 16), int(memory_size), BLOCK_SIZE) # [STATE] chunks = [(32768, 200)] [/STATE]\n for chunk in chunks: # [STATE] chunk = (32768, 200) [/STATE]\n dump.extend(bytearray(api.memory_dump(chunk[0], chunk[1]))) # [STATE] dump = bytearray(b'\\x00') [/STATE]\n\n # append the results to the destination file\n with open(destination, 'wb') as f: # [STATE] f = [/STATE]\n f.write(dump)\n\n click.secho('Memory dumped to file: {0}'.format(destination), fg='green')\n\ndump_from_base(['0x00008000', '200', '/foo'])", "loop_code": "1: def dump_from_base(args: list) -> None:\n2: \"\"\"\n3: Dump memory from a base address for a specific size to file\n4:\n5: :param args:\n6: :return:\n7: \"\"\"\n8:\n9: if len(clean_argument_flags(args)) < 3:\n10: click.secho('Usage: memory dump from_base ', bold=True)\n11: return\n12:\n13: # the destination file to write the dump to\n14: base_address = args[0]\n15: memory_size = args[1]\n16: destination = args[2]\n17:\n18: # Check for file override\n19: if os.path.exists(destination):\n20: click.secho('Destination file {dest} already exists'.format(dest=destination), fg='yellow', bold=True)\n21: if not click.confirm('Override?'):\n22: return\n23:\n24: click.secho('Dumping {0} from {1} to {2}'.format(sizeof_fmt(int(memory_size)), base_address, destination),\n25: fg='green', dim=True)\n26:\n27: api = state_connection.get_api()\n28:\n29: # iirc, if you don't cast the return type to a bytearray it uses the sizeof(int) per cell, which is massive\n30: dump = bytearray()\n31: chunks = _get_chunks(int(base_address, 16), int(memory_size), BLOCK_SIZE)\n32: for chunk in chunks:\n33: dump.extend(bytearray(api.memory_dump(chunk[0], chunk[1])))\n34:\n35: # append the results to the destination file\n36: with open(destination, 'wb') as f:\n37: f.write(dump)\n38:\n39: click.secho('Memory dumped to file: {0}'.format(destination), fg='green')\n40:\n41: dump_from_base(['0x00008000', '200', '/foo'])", "question": "What is the value of 'f' in line 36 after executing 'dump_from_base(['0x00008000', '200', '/foo'])'?", "answer": "", "variable_assignment": "f = ", "loop_range": [32, 33], "post_loop_line": 36} {"idx": 25, "scratchpad_format": "def _a1_to_rowcol_unbounded(label):\n \"\"\"Translates a cell's address in A1 notation to a tuple of integers.\n\n Same as `a1_to_rowcol()` but allows for missing row or column part\n (e.g. \"A\" for the first column)\n\n :returns: a tuple containing `row` and `column` numbers. Both indexed\n from 1 (one).\n :rtype: tuple\n\n Example:\n\n >>> _a1_to_rowcol_unbounded('A1')\n (1, 1)\n\n >>> _a1_to_rowcol_unbounded('A')\n (inf, 1)\n\n >>> _a1_to_rowcol_unbounded('1')\n (1, inf)\n\n >>> _a1_to_rowcol_unbounded('ABC123')\n (123, 731)\n\n >>> _a1_to_rowcol_unbounded('ABC')\n (inf, 731)\n\n >>> _a1_to_rowcol_unbounded('123')\n (123, inf)\n\n >>> _a1_to_rowcol_unbounded('1A')\n Traceback (most recent call last):\n ...\n gspread.exceptions.IncorrectCellLabel: 1A\n\n >>> _a1_to_rowcol_unbounded('')\n (inf, inf)\n\n \"\"\"\n m = A1_ADDR_ROW_COL_RE.match(label) # [STATE] m = [/STATE]\n if m:\n column_label, row = m.groups() # [STATE] column_label = 'A' [/STATE] # [STATE] row = '1' [/STATE]\n\n if column_label:\n col = 0 # [STATE] col = 0 [/STATE]\n for i, c in enumerate(reversed(column_label.upper())): # [STATE] i = 0 [/STATE] [STATE] c = 'A' [/STATE]\n col += (ord(c) - MAGIC_NUMBER) * (26**i) # [STATE] col = 1 [/STATE]\n else:\n col = inf\n\n if row:\n row = int(row) # [STATE] row = 1 [/STATE]\n else:\n row = inf\n else:\n raise IncorrectCellLabel(label)\n\n return (row, col)\n\n_a1_to_rowcol_unbounded('A1')", "loop_code": "1: def _a1_to_rowcol_unbounded(label):\n2: \"\"\"Translates a cell's address in A1 notation to a tuple of integers.\n3:\n4: Same as `a1_to_rowcol()` but allows for missing row or column part\n5: (e.g. \"A\" for the first column)\n6:\n7: :returns: a tuple containing `row` and `column` numbers. Both indexed\n8: from 1 (one).\n9: :rtype: tuple\n10:\n11: Example:\n12:\n13: >>> _a1_to_rowcol_unbounded('A1')\n14: (1, 1)\n15:\n16: >>> _a1_to_rowcol_unbounded('A')\n17: (inf, 1)\n18:\n19: >>> _a1_to_rowcol_unbounded('1')\n20: (1, inf)\n21:\n22: >>> _a1_to_rowcol_unbounded('ABC123')\n23: (123, 731)\n24:\n25: >>> _a1_to_rowcol_unbounded('ABC')\n26: (inf, 731)\n27:\n28: >>> _a1_to_rowcol_unbounded('123')\n29: (123, inf)\n30:\n31: >>> _a1_to_rowcol_unbounded('1A')\n32: Traceback (most recent call last):\n33: ...\n34: gspread.exceptions.IncorrectCellLabel: 1A\n35:\n36: >>> _a1_to_rowcol_unbounded('')\n37: (inf, inf)\n38:\n39: \"\"\"\n40: m = A1_ADDR_ROW_COL_RE.match(label)\n41: if m:\n42: column_label, row = m.groups()\n43:\n44: if column_label:\n45: col = 0\n46: for i, c in enumerate(reversed(column_label.upper())):\n47: col += (ord(c) - MAGIC_NUMBER) * (26**i)\n48: else:\n49: col = inf\n50:\n51: if row:\n52: row = int(row)\n53: else:\n54: row = inf\n55: else:\n56: raise IncorrectCellLabel(label)\n57:\n58: return (row, col)\n59:\n60: _a1_to_rowcol_unbounded('A1')", "question": "What is the value of 'row' in line 52 after executing '_a1_to_rowcol_unbounded('A1')'?", "answer": "1", "variable_assignment": "row = 1", "loop_range": [46, 47], "post_loop_line": 52} {"idx": 26, "scratchpad_format": "def test_multithreading_lock(execution_number): # type: ignore[misc]\n \"\"\"Reruns test multiple times since error is random and\n depends on CPU and can lead to false positive result.\n\n \"\"\"\n n_threads = 10 # [STATE] n_threads = 10 [/STATE]\n n_requests = 30 # [STATE] n_requests = 30 [/STATE]\n with responses.RequestsMock() as m: # [STATE] m = {_calls=, _registry=, passthru_prefixes=(), assert_all_requests_are_fired=True, response_callback=None, target='requests.adapters.HTTPAdapter.send', _patcher=, _thread_lock=} [/STATE]\n for j in range(n_threads): # [STATE] j = 0 [/STATE] [STATE] j = 1 [/STATE] [STATE] j = 2 [/STATE] [STATE] j = 3 [/STATE] [STATE] j = 4 [/STATE] [STATE] j = 5 [/STATE] [STATE] j = 6 [/STATE] [STATE] j = 7 [/STATE] [STATE] j = 8 [/STATE] [STATE] j = 9 [/STATE]\n for i in range(n_requests): # [STATE] i = 0 [/STATE] [STATE] i = 1 [/STATE] [STATE] i = 2 [/STATE] [STATE] i = 3 [/STATE] [STATE] i = 4 [/STATE] [STATE] i = 5 [/STATE] [STATE] i = 6 [/STATE] [STATE] i = 7 [/STATE] [STATE] i = 8 [/STATE] [STATE] i = 9 [/STATE] [STATE] i = 10 [/STATE] [STATE] i = 11 [/STATE] [STATE] i = 12 [/STATE] [STATE] i = 13 [/STATE] [STATE] i = 14 [/STATE] [STATE] i = 15 [/STATE] [STATE] i = 16 [/STATE] [STATE] i = 17 [/STATE] [STATE] i = 18 [/STATE] [STATE] i = 19 [/STATE] [STATE] i = 20 [/STATE]\n m.add(url=f\"http://example.com/example{i}\", method=\"GET\")\n\n def fun(): # [STATE] fun = .fun at 0x7f683d0139d0> [/STATE]\n for req in range(n_requests):\n requests.get(f\"http://example.com/example{req}\")\n\n threads = [ # [STATE] threads = [, , , , , , , , , ] [/STATE]\n threading.Thread(name=f\"example{i}\", target=fun) for i in range(n_threads)\n ]\n for thread in threads: # [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE]\n thread.start() # [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] m = {_calls=, _registry=, passthru_prefixes=(), assert_all_requests_are_fired=True, response_callback=None, target='requests.adapters.HTTPAdapter.send', _patcher=, _thread_lock=} [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] m = {_calls=, _registry=, passthru_prefixes=(), assert_all_requests_are_fired=True, response_callback=None, target='requests.adapters.HTTPAdapter.send', _patcher=, _thread_lock=} [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE]\n for thread in threads: # [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] thread = [/STATE] [STATE] m = {_calls=, _registry=, passthru_prefixes=(), assert_all_requests_are_fired=True, response_callback=None, target='requests.adapters.HTTPAdapter.send', _patcher=None, _thread_lock=} [/STATE]\n thread.join() # [STATE] m = {_calls=, _registry=, passthru_prefixes=(), assert_all_requests_are_fired=True, response_callback=None, target='requests.adapters.HTTPAdapter.send', _patcher=, _thread_lock=} [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE] [STATE] threads = [, , , , , , , , , ] [/STATE] [STATE] thread = [/STATE]\n\ntest_multithreading_lock(0)", "loop_code": "1: def test_multithreading_lock(execution_number): # type: ignore[misc]\n2: \"\"\"Reruns test multiple times since error is random and\n3: depends on CPU and can lead to false positive result.\n4:\n5: \"\"\"\n6: n_threads = 10\n7: n_requests = 30\n8: with responses.RequestsMock() as m:\n9: for j in range(n_threads):\n10: for i in range(n_requests):\n11: m.add(url=f\"http://example.com/example{i}\", method=\"GET\")\n12:\n13: def fun():\n14: for req in range(n_requests):\n15: requests.get(f\"http://example.com/example{req}\")\n16:\n17: threads = [\n18: threading.Thread(name=f\"example{i}\", target=fun) for i in range(n_threads)\n19: ]\n20: for thread in threads:\n21: thread.start()\n22: for thread in threads:\n23: thread.join()\n24:\n25: test_multithreading_lock(0)", "question": "What is the value of 'threads' in line 17 after executing 'test_multithreading_lock(0)'?", "answer": "[, , , , , , , , , ]", "variable_assignment": "threads = [, , , , , , , , , ]", "loop_range": [14, 15], "post_loop_line": 17} {"idx": 27, "scratchpad_format": "def _clean_unicode(url: str) -> str:\n \"\"\"Clean up URLs, which use punycode to handle unicode chars.\n\n Applies percent encoding to URL path and query if required.\n\n Parameters\n ----------\n url : str\n URL that should be cleaned from unicode\n\n Returns\n -------\n str\n Cleaned URL\n\n \"\"\"\n urllist = list(urlsplit(url)) # [STATE] urllist = ['http', 'example.com', '/test', 'type=2&ie=utf8&query=\u6c49\u5b57', ''] [/STATE]\n netloc = urllist[1] # [STATE] netloc = 'example.com' [/STATE]\n if _has_unicode(netloc):\n domains = netloc.split(\".\")\n for i, d in enumerate(domains):\n if _has_unicode(d):\n d = \"xn--\" + d.encode(\"punycode\").decode(\"ascii\")\n domains[i] = d\n urllist[1] = \".\".join(domains)\n url = urlunsplit(urllist)\n\n # Clean up path/query/params, which use url-encoding to handle unicode chars\n chars = list(url) # [STATE] chars = ['h', 't', 't', 'p', ':', '/', '/', 'e', 'x', 'a', 'm', 'p', 'l', 'e', '.', 'c', 'o', 'm', '/', 't', 'e', 's', 't', '?', 't', 'y', 'p', 'e', '=', '2', '&', 'i', 'e', '=', 'u', 't', 'f', '8', '&', 'q', 'u', 'e', 'r', 'y', '=', '\u6c49', '\u5b57'] [/STATE]\n for i, x in enumerate(chars): # [STATE] i = 0 [/STATE] [STATE] x = 'h' [/STATE] [STATE] i = 1 [/STATE] [STATE] x = 't' [/STATE] [STATE] i = 2 [/STATE] [STATE] i = 3 [/STATE] [STATE] x = 'p' [/STATE] [STATE] i = 4 [/STATE] [STATE] x = ':' [/STATE] [STATE] i = 5 [/STATE] [STATE] x = '/' [/STATE] [STATE] i = 6 [/STATE] [STATE] i = 7 [/STATE] [STATE] x = 'e' [/STATE] [STATE] i = 8 [/STATE] [STATE] x = 'x' [/STATE] [STATE] i = 9 [/STATE] [STATE] x = 'a' [/STATE] [STATE] i = 10 [/STATE] [STATE] x = 'm' [/STATE] [STATE] i = 11 [/STATE]\n if ord(x) > 128:\n chars[i] = quote(x) # [STATE] chars = ['h', 't', 't', 'p', ':', '/', '/', 'e', 'x', 'a', 'm', 'p', 'l', 'e', '.', 'c', 'o', 'm', '/', 't', 'e', 's', 't', '?', 't', 'y', 'p', 'e', '=', '2', '&', 'i', 'e', '=', 'u', 't', 'f', '8', '&', 'q', 'u', 'e', 'r', 'y', '=', '%E6%B1%89', '\u5b57'] [/STATE] [STATE] chars = ['h', 't', 't', 'p', ':', '/', '/', 'e', 'x', 'a', 'm', 'p', 'l', 'e', '.', 'c', 'o', 'm', '/', 't', 'e', 's', 't', '?', 't', 'y', 'p', 'e', '=', '2', '&', 'i', 'e', '=', 'u', 't', 'f', '8', '&', 'q', 'u', 'e', 'r', 'y', '=', '%E6%B1%89', '%E5%AD%97'] [/STATE]\n\n return \"\".join(chars)\n\n_clean_unicode('http://example.com/test?type=2&ie=utf8&query=\u6c49\u5b57')", "loop_code": "1: def _clean_unicode(url: str) -> str:\n2: \"\"\"Clean up URLs, which use punycode to handle unicode chars.\n3:\n4: Applies percent encoding to URL path and query if required.\n5:\n6: Parameters\n7: ----------\n8: url : str\n9: URL that should be cleaned from unicode\n10:\n11: Returns\n12: -------\n13: str\n14: Cleaned URL\n15:\n16: \"\"\"\n17: urllist = list(urlsplit(url))\n18: netloc = urllist[1]\n19: if _has_unicode(netloc):\n20: domains = netloc.split(\".\")\n21: for i, d in enumerate(domains):\n22: if _has_unicode(d):\n23: d = \"xn--\" + d.encode(\"punycode\").decode(\"ascii\")\n24: domains[i] = d\n25: urllist[1] = \".\".join(domains)\n26: url = urlunsplit(urllist)\n27:\n28: # Clean up path/query/params, which use url-encoding to handle unicode chars\n29: chars = list(url)\n30: for i, x in enumerate(chars):\n31: if ord(x) > 128:\n32: chars[i] = quote(x)\n33:\n34: return \"\".join(chars)\n35:\n36: _clean_unicode('http://example.com/test?type=2&ie=utf8&query=\u6c49\u5b57')", "question": "What is the value of 'chars' in line 29 after executing '_clean_unicode('http://example.com/test?type=2&ie=utf8&query=\u6c49\u5b57')'?", "answer": "['h', 't', 't', 'p', ':', '/', '/', 'e', 'x', 'a', 'm', 'p', 'l', 'e', '.', 'c', 'o', 'm', '/', 't', 'e', 's', 't', '?', 't', 'y', 'p', 'e', '=', '2', '&', 'i', 'e', '=', 'u', 't', 'f', '8', '&', 'q', 'u', 'e', 'r', 'y', '=', '\u6c49', '\u5b57']", "variable_assignment": "chars = ['h', 't', 't', 'p', ':', '/', '/', 'e', 'x', 'a', 'm', 'p', 'l', 'e', '.', 'c', 'o', 'm', '/', 't', 'e', 's', 't', '?', 't', 'y', 'p', 'e', '=', '2', '&', 'i', 'e', '=', 'u', 't', 'f', '8', '&', 'q', 'u', 'e', 'r', 'y', '=', '\u6c49', '\u5b57']", "loop_range": [21, 24], "post_loop_line": 29}