{ "cells": [ { "cell_type": "code", "execution_count": 26, "id": "72566cbd", "metadata": {}, "outputs": [], "source": [ "import re\n", "from typing import Dict, List, Optional\n", "from mathruler.grader import extract_boxed_content, grade_answer\n", "import json\n", "from pathlib import Path\n", "from typing import List, Dict, Union\n", "from typing import Dict, List, Any\n", "import re\n", "from typing import List\n", "import json, logging\n", "from pathlib import Path\n", "from typing import List, Dict, Union\n", "log = logging.getLogger(__name__)\n", "import json\n", "from typing import Iterator, List, Dict\n", "from mathruler.grader import extract_boxed_content\n", "from typing import Union, Dict\n", "from PIL import Image\n", "from IPython.display import display\n", "import io\n", "from PIL import Image\n", "from IPython.display import display\n", "import io, base64\n", "import numpy as np\n", "from typing import Any\n", "\n", "\n", "def iter_jsonl(path: str) -> Iterator[Dict]:\n", " \"\"\"Yield one JSON object per line from a .jsonl file.\"\"\"\n", " with open(path, 'r', encoding='utf-8') as f:\n", " for line in f:\n", " line = line.strip()\n", " if not line:\n", " continue\n", " yield json.loads(line)\n", "\n", "def load_jsonl(path: str) -> List[Dict]:\n", " \"\"\"Read an entire .jsonl file into a list of dicts.\"\"\"\n", " return list(iter_jsonl(path))\n", "\n", "def show_image_from_bytes(item: Union[bytes, bytearray, Dict[str, object]]):\n", " \"\"\"\n", " Display an image from raw bytes or from a dict containing a 'bytes' key.\n", " Returns the PIL.Image.Image object.\n", " \"\"\"\n", " # Accept either raw bytes or {'bytes': ..., 'path': ...}\n", " data = item['bytes'] if isinstance(item, dict) and 'bytes' in item else item\n", " if not isinstance(data, (bytes, bytearray)):\n", " raise TypeError(\"Expected raw image bytes or a dict with a 'bytes' key.\")\n", "\n", " img = Image.open(io.BytesIO(data))\n", " img.load() # fully decode\n", " display(img) # nice inline display in notebooks\n", " return img\n", "\n", "def _extract_bytes(x: Any):\n", " # dict forms\n", " if isinstance(x, dict):\n", " if 'bytes' in x and isinstance(x['bytes'], (bytes, bytearray, memoryview)):\n", " return bytes(x['bytes'])\n", " if 'image' in x: # nested image dict\n", " return _extract_bytes(x['image'])\n", " if 'b64' in x and isinstance(x['b64'], str):\n", " return base64.b64decode(x['b64'])\n", " if 'data' in x and isinstance(x['data'], str) and x['data'].startswith('data:image'):\n", " return base64.b64decode(x['data'].split(',', 1)[1])\n", " if 'path' in x and isinstance(x['path'], str):\n", " with open(x['path'], 'rb') as f:\n", " return f.read()\n", " # list/tuple wrapper\n", " if isinstance(x, (list, tuple)) and len(x) > 0:\n", " return _extract_bytes(x[0])\n", " # raw bytes-ish\n", " if isinstance(x, (bytes, bytearray, memoryview)):\n", " return bytes(x)\n", " # string path or data URL\n", " if isinstance(x, str):\n", " if x.startswith('data:image'):\n", " return base64.b64decode(x.split(',', 1)[1])\n", " try:\n", " with open(x, 'rb') as f:\n", " return f.read()\n", " except Exception:\n", " pass\n", " # file-like\n", " if hasattr(x, 'read'):\n", " return x.read()\n", " return None\n", "\n", "def show_image_any(x: Any):\n", " \"\"\"Display an image from many possible formats (bytes, dicts, lists, paths, PIL, numpy).\"\"\"\n", " if isinstance(x, Image.Image):\n", " display(x); return x\n", " if isinstance(x, np.ndarray):\n", " img = Image.fromarray(x); display(img); return img\n", "\n", " data = _extract_bytes(x)\n", " if data is None:\n", " kind = type(x)\n", " keys = list(x.keys()) if isinstance(x, dict) else None\n", " raise TypeError(f\"Unsupported image format: {kind} {('keys='+str(keys)) if keys else ''}\")\n", "\n", " img = Image.open(io.BytesIO(data))\n", " img.load()\n", " display(img)\n", " return img\n", "\n", "def read_json(\n", " path: Union[str, Path],\n", " *,\n", " skip_bad_lines: bool = True,\n", " verbose: bool = False,\n", ") -> List[Dict]:\n", " \"\"\"\n", " Load either a JSON array or a JSON-Lines (JSONL) file.\n", "\n", " Parameters\n", " ----------\n", " path : str or Path\n", " File to read.\n", " skip_bad_lines : bool, default True\n", " For JSONL: if True, ignore lines that raise `json.JSONDecodeError`;\n", " if False, re-raise.\n", " verbose : bool, default False\n", " Log line numbers of skipped lines.\n", "\n", " Returns\n", " -------\n", " list[dict]\n", " \"\"\"\n", " path = Path(path).expanduser()\n", "\n", " with path.open(\"r\", encoding=\"utf-8\") as f:\n", " first_non_ws = f.read(1).lstrip()\n", " f.seek(0)\n", "\n", " # --- Case 1: JSON array (starts with '[') --------------------------\n", " if first_non_ws.startswith(\"[\"):\n", " data = json.load(f)\n", " if not isinstance(data, list):\n", " raise ValueError(\"Top-level JSON is not an array.\")\n", " if not all(isinstance(item, dict) for item in data):\n", " raise ValueError(\"Not every element is an object.\")\n", " return data\n", "\n", " # --- Case 2: JSON-Lines -------------------------------------------\n", " records: List[Dict] = []\n", " for lineno, line in enumerate(f, 1):\n", " line = line.strip()\n", " if not line: # skip blank lines\n", " continue\n", " try:\n", " obj = json.loads(line)\n", " if isinstance(obj, dict):\n", " records.append(obj)\n", " else:\n", " if verbose:\n", " log.warning(\"Line %d is not a JSON object; skipped\", lineno)\n", " except json.JSONDecodeError:\n", " if skip_bad_lines:\n", " if verbose:\n", " log.warning(\"Malformed JSON at line %d; skipped\", lineno)\n", " continue\n", " else:\n", " raise\n", " return records\n", "\n", "def accuracy_reward(predict: str, ground_truth: str) -> float:\n", " answer = extract_boxed_content(predict)\n", " # answer = extract_answer(predict)\n", " return 1.0 if grade_answer(answer, ground_truth) else 0.0\n", "\n", "def extract_description(predict: str) -> Optional[str]:\n", " \"\"\"\n", " Extracts the content of the block from `predict`.\n", " Returns the inner text (with leading/trailing whitespace stripped),\n", " or None if no tag is found.\n", " \"\"\"\n", " match = re.search(r\"([\\s\\S]*?)\", predict, re.DOTALL)\n", " if not match:\n", " return None\n", " return match.group(1).strip()\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "e90f4a93", "metadata": {}, "outputs": [], "source": [ "captions = read_json('./gemini-flash/MLLM_rlvr_train.json')\n", "# caption_ans = read_json('./caption_out/MLLM_rlvr_train.json')" ] }, { "cell_type": "code", "execution_count": 35, "id": "06d20ccb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "62126" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_ans = read_json('./caption_out/MLLM_rlvr_train.json')\n", "len(caption_ans)" ] }, { "cell_type": "code", "execution_count": 28, "id": "1ae747ac", "metadata": {}, "outputs": [], "source": [ "from datasets import load_dataset\n", "\n", "raw_data = load_dataset('zli12321/MLLM_rlvr_train')" ] }, { "cell_type": "code", "execution_count": 30, "id": "a05429a9", "metadata": {}, "outputs": [], "source": [ "# show_image_any(raw_data['train'][0]['images'])" ] }, { "cell_type": "code", "execution_count": 31, "id": "e0391721", "metadata": {}, "outputs": [], "source": [ "indices = [ele['index'] for ele in captions]" ] }, { "cell_type": "code", "execution_count": 32, "id": "a22b785b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DatasetDict({\n", " train: Dataset({\n", " features: ['problem', 'answer', 'images'],\n", " num_rows: 75340\n", " })\n", "})" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data" ] }, { "cell_type": "code", "execution_count": 33, "id": "ee5b2b99", "metadata": {}, "outputs": [], "source": [ "from datasets import Dataset, DatasetDict \n", "\n", "subset = raw_data[\"train\"].select(indices) # returns a *new* Dataset\n", "\n", "# If you still want it wrapped in a DatasetDict:\n", "subset_data = DatasetDict(train=subset)" ] }, { "cell_type": "code", "execution_count": 34, "id": "b057f9f7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "DatasetDict({\n", " train: Dataset({\n", " features: ['problem', 'answer', 'images'],\n", " num_rows: 62126\n", " })\n", "})" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "subset_data" ] }, { "cell_type": "code", "execution_count": 22, "id": "0111b9e6", "metadata": {}, "outputs": [], "source": [ "questions = subset_data['train']['problem']" ] }, { "cell_type": "code", "execution_count": 36, "id": "e5eba578", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'index': 10070,\n", " 'problem': 'What does the variable \\\\( \\\\lambda_s + d\\\\lambda \\\\) represent in the context of this figure? Options:\\nA. The initial wavelength of a light ray before entering the medium.\\nB. The change in wavelength of a light ray as it passes through a medium.\\nC. The wavelength of a light ray after passing through a differential length of the medium.\\nD. The constant wavelength of a light ray in a vacuum.',\n", " 'solution': 'C',\n", " 'predictions': [\"The image depicts a light ray traveling along a curved path. The path is bounded by two black lines, representing the edges of a medium. The light ray originates at point 'o' where λ = 0. The ray passes through a small cylindrical volume element at point 's'. The image labels λ_s as the affine parameter at point 's', and λ_s + dλ as the affine parameter after passing through the differential length of the medium. The length of the path segment within the volume element is denoted as dl_s, and the cross-sectional area of the volume element is dS_s. The change in the affine parameter is δλ_s. The image also shows λ_g at point 'g' and k^μ. \\nThe question asks what λ_s + dλ represents. From the image, we can see that λ_s is the affine parameter at point 's', and λ_s + dλ is the affine parameter after the light ray has passed through a differential length of the medium. Since the affine parameter is related to the wavelength, λ_s + dλ represents the wavelength of the light ray after passing through a differential length of the medium. Therefore, the correct answer is C.\\n\\nA is incorrect because λ=0 at point 'o', which is the initial point.\\nB is incorrect because dλ represents the change in the affine parameter, not necessarily the wavelength.\\nD is incorrect because the light ray is traveling through a medium, not a vacuum.\\n\\n\\\\boxed{C}\"]}" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "captions[9000]" ] }, { "cell_type": "code", "execution_count": 37, "id": "bd01af95", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'index': 10070,\n", " 'problem': 'What does the variable \\\\( \\\\lambda_s + d\\\\lambda \\\\) represent in the context of this figure? Options:\\nA. The initial wavelength of a light ray before entering the medium.\\nB. The change in wavelength of a light ray as it passes through a medium.\\nC. The wavelength of a light ray after passing through a differential length of the medium.\\nD. The constant wavelength of a light ray in a vacuum.',\n", " 'solution': 'C',\n", " 'predictions': [\"The image depicts a light ray traveling along a curved path. The path is bounded by two black lines, representing the edges of a medium. The light ray originates at point 'o' where λ = 0. The ray passes through a small cylindrical volume element at point 's'. The image labels λ_s as the affine parameter at point 's', and λ_s + dλ as the affine parameter after passing through the differential length of the medium. The length of the path segment within the volume element is denoted as dl_s, and the cross-sectional area of the volume element is dS_s. The change in the affine parameter is δλ_s. The image also shows λ_g at point 'g' and k^μ. \\nThe question asks what λ_s + dλ represents. From the image, we can see that λ_s is the affine parameter at point 's', and λ_s + dλ is the affine parameter after the light ray has passed through a differential length of the medium. Since the affine parameter is related to the wavelength, λ_s + dλ represents the wavelength of the light ray after passing through a differential length of the medium. Therefore, the correct answer is C.\\n\\nA is incorrect because λ=0 at point 'o', which is the initial point.\\nB is incorrect because dλ represents the change in the affine parameter, not necessarily the wavelength.\\nD is incorrect because the light ray is traveling through a medium, not a vacuum.\\n\\n\\\\boxed{C}\"],\n", " 'model': 'Qwen2.5-VL-72B-Instruct',\n", " 'model_caption_response': \"\\nTo determine what \\\\( \\\\lambda_s + d\\\\lambda \\\\) represents, let's analyze the given information:\\n\\n1. The light ray starts at point 'o' with \\\\( \\\\lambda = 0 \\\\).\\n2. At point 's', the affine parameter is labeled as \\\\( \\\\lambda_s \\\\).\\n3. After passing through a differential length of the medium, the affine parameter changes to \\\\( \\\\lambda_s + d\\\\lambda \\\\).\\n\\nThe term \\\\( d\\\\lambda \\\\) indicates a small change in the affine parameter \\\\( \\\\lambda \\\\). Therefore, \\\\( \\\\lambda_s + d\\\\lambda \\\\) represents the value of the affine parameter after the light ray has traveled a small distance \\\\( dl_s \\\\) within the medium.\\n\\nGiven these points, \\\\( \\\\lambda_s + d\\\\lambda \\\\) corresponds to the updated value of the affine parameter after the light ray has passed through a differential length of the medium.\\n\\nThus, the correct interpretation is that \\\\( \\\\lambda_s + d\\\\lambda \\\\) represents the wavelength of a light ray after passing through a differential length of the medium.\\n\\n\\\\boxed{C}\"}" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_ans[9000]" ] }, { "cell_type": "code", "execution_count": 40, "id": "fc22fbc1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'problem': 'What does the variable \\\\( \\\\lambda_s + d\\\\lambda \\\\) represent in the context of this figure? Options:\\nA. The initial wavelength of a light ray before entering the medium.\\nB. The change in wavelength of a light ray as it passes through a medium.\\nC. The wavelength of a light ray after passing through a differential length of the medium.\\nD. The constant wavelength of a light ray in a vacuum.',\n", " 'answer': 'C',\n", " 'images': }" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "subset_data['train'][9000]" ] }, { "cell_type": "code", "execution_count": 15, "id": "8bd16d08", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'index': 564, 'problem': 'During this time, thermal energy was transferred from () to (). Options:\\nA. the surroundings . . . each cake\\nB. each cake . . . the surroundings', 'solution': 'B', 'predictions': ['The image is a table with three columns and two rows of data. The first column is labeled \"Cake\" and lists \"Cake in the pan\" and \"Cake on the plate\". The second column is labeled \"Initial temperature (°C)\" and lists \"92\" for both cake types. The third column is labeled \"Final temperature (°C)\" and lists \"82\" for \"Cake in the pan\" and \"79\" for \"Cake on the plate\". The temperature of both cakes decreased over time.\\nThe question asks about the direction of thermal energy transfer. Since the initial temperature of both cakes is 92°C and the final temperatures are lower (82°C and 79°C), thermal energy must have been transferred from the cakes to the surroundings. Therefore, the correct answer is B.\\n\\\\boxed{B}'], 'model': 'Qwen2.5-VL-72B-Instruct', 'model_caption_response': '\\nTo determine the direction of thermal energy transfer, we need to consider the change in temperature of the cakes.\\n\\n1. Both cakes started at an initial temperature of 92°C.\\n2. After some time, the temperature of the \"Cake in the pan\" decreased to 82°C, and the \"Cake on the plate\" decreased to 79°C.\\n3. Since the final temperatures are lower than the initial temperatures, it indicates that the cakes lost thermal energy.\\n4. Thermal energy always flows from a hotter object to a cooler object until thermal equilibrium is reached.\\n5. Therefore, the thermal energy must have been transferred from the cakes (which were hotter) to the surroundings (which were cooler).\\n\\nBased on this reasoning, the correct option is B.\\n\\n\\\\boxed{B}'}\n" ] }, { "data": { "image/jpeg": 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", 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", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 351\n", "count, want = 0, 500\n", "for i in range(len(caption_ans)):\n", " # print(caption_ans[i])\n", " solution = caption_ans[i]['solution']\n", " prediction_answer = caption_ans[i]['predictions'][0]\n", " caption_answer = caption_ans[i]['model_caption_response']\n", " accuracy = accuracy_reward(prediction_answer, solution)\n", " accuracy1 = accuracy_reward(caption_answer, solution)\n", " \n", " if count >= want and accuracy == 1 and accuracy1 == 1:\n", " print(caption_ans[i])\n", " show_image_any(subset_data['train'][i]['images'])\n", " break\n", " \n", " count += 1" ] }, { "cell_type": "code", "execution_count": 16, "id": "5ef6347c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'index': 564,\n", " 'problem': 'During this time, thermal energy was transferred from () to (). Options:\\nA. the surroundings . . . each cake\\nB. each cake . . . the surroundings',\n", " 'solution': 'B',\n", " 'predictions': ['The image is a table with three columns and two rows of data. The first column is labeled \"Cake\" and lists \"Cake in the pan\" and \"Cake on the plate\". The second column is labeled \"Initial temperature (°C)\" and lists \"92\" for both cake types. The third column is labeled \"Final temperature (°C)\" and lists \"82\" for \"Cake in the pan\" and \"79\" for \"Cake on the plate\". The temperature of both cakes decreased over time.\\nThe question asks about the direction of thermal energy transfer. Since the initial temperature of both cakes is 92°C and the final temperatures are lower (82°C and 79°C), thermal energy must have been transferred from the cakes to the surroundings. Therefore, the correct answer is B.\\n\\\\boxed{B}'],\n", " 'model': 'Qwen2.5-VL-72B-Instruct',\n", " 'model_caption_response': '\\nTo determine the direction of thermal energy transfer, we need to consider the change in temperature of the cakes.\\n\\n1. Both cakes started at an initial temperature of 92°C.\\n2. After some time, the temperature of the \"Cake in the pan\" decreased to 82°C, and the \"Cake on the plate\" decreased to 79°C.\\n3. Since the final temperatures are lower than the initial temperatures, it indicates that the cakes lost thermal energy.\\n4. Thermal energy always flows from a hotter object to a cooler object until thermal equilibrium is reached.\\n5. Therefore, the thermal energy must have been transferred from the cakes (which were hotter) to the surroundings (which were cooler).\\n\\nBased on this reasoning, the correct option is B.\\n\\n\\\\boxed{B}'}" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_ans[i]" ] }, { "cell_type": "code", "execution_count": null, "id": "02ef91de", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "21195" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from tqdm import tqdm\n", "\n", "count = 0\n", "for i in range(len(caption_ans)):\n", " # print(caption_ans[i])\n", " solution = caption_ans[i]['solution']\n", " prediction_answer = caption_ans[i]['predictions'][0]\n", " caption_answer = caption_ans[i]['model_caption_response']\n", " accuracy = accuracy_reward(prediction_answer, solution)\n", " accuracy1 = accuracy_reward(caption_answer, solution)\n", " \n", " if accuracy == 1 and accuracy1 == 1:\n", " # print(caption_ans[i])\n", " # show_image_any(subset_data['train'][i]['images'])\n", " # break\n", " \n", " count += 1\n", " \n", "count" ] }, { "cell_type": "code", "execution_count": 42, "id": "53e67a6f", "metadata": {}, "outputs": [ { "data": { "image/jpeg": 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", 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", "text/plain": [ "" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "subset_data['train'][i]['images']" ] }, { "cell_type": "code", "execution_count": 43, "id": "7ba27c0c", "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "from typing import Union\n", "from PIL import Image\n", "import PIL\n", "import numpy\n", "\n", "def save_image(\n", " img: Union[\"PIL.Image.Image\", \"numpy.ndarray\", bytes],\n", " folder: str | Path,\n", " filename: str,\n", " *,\n", " pil_format: str | None = None,\n", " **save_kwargs,\n", ") -> Path:\n", " \"\"\"\n", " Save an image to `folder/filename`.\n", "\n", " Parameters\n", " ----------\n", " img : PIL.Image.Image | numpy.ndarray | bytes\n", " • PIL Image – saved via `Image.save` \n", " • NumPy array (BGR or RGB) – saved via `cv2.imwrite` \n", " • Raw bytes – written directly\n", " folder : destination directory (created if needed)\n", " filename : file name with extension, e.g. 'pic.jpg'\n", " pil_format : explicit format for PIL images, e.g. 'PNG' (optional)\n", " **save_kwargs\n", " Extra kwargs passed to PIL's `save` (quality=95, optimize=True, …)\n", "\n", " Returns\n", " -------\n", " Path to the saved file.\n", " \"\"\"\n", " folder = Path(folder)\n", " folder.mkdir(parents=True, exist_ok=True)\n", " path = folder / filename\n", "\n", " # Lazy imports to keep dependencies optional\n", " if isinstance(img, bytes):\n", " path.write_bytes(img)\n", "\n", " else:\n", " try:\n", " from PIL import Image # type: ignore\n", " except ImportError as e:\n", " raise ImportError(\"PIL (Pillow) is required for this function\") from e\n", "\n", " if isinstance(img, Image.Image):\n", " img.save(path, format=pil_format, **save_kwargs)\n", " else: # assume NumPy array (cv2 / OpenCV style)\n", " try:\n", " import cv2 # type: ignore\n", " except ImportError as e:\n", " raise ImportError(\"OpenCV (cv2) is required for saving NumPy images\") from e\n", " cv2.imwrite(str(path), img)\n", "\n", " return path\n" ] }, { "cell_type": "code", "execution_count": 46, "id": "c634554c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "PosixPath('cold_start/10.jpg')" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "save_image(subset_data['train'][10]['images'], './cold_start', '10.jpg')" ] }, { "cell_type": "code", "execution_count": null, "id": "6e48f48a", "metadata": {}, "outputs": [], "source": [ "# 'index': 564,\n", "# 'problem': 'During this time, thermal energy was transferred from () to (). Options:\\nA. the surroundings . . . each cake\\nB. each cake . . . the surroundings',\n", "# 'solution': 'B',\n", "# 'predictions': ['The image is a table with three columns and two rows of data. The first column is labeled \"Cake\" and lists \"Cake in the pan\" and \"Cake on the plate\". The second column is labeled \"Initial temperature (°C)\" and lists \"92\" for both cake types. The third column is labeled \"Final temperature (°C)\" and lists \"82\" for \"Cake in the pan\" and \"79\" for \"Cake on the plate\". The temperature of both cakes decreased over time.\\nThe question asks about the direction of thermal energy transfer. Since the initial temperature of both cakes is 92°C and the final temperatures are lower (82°C and 79°C), thermal energy must have been transferred from the cakes to the surroundings. Therefore, the correct answer is B.\\n\\\\boxed{B}'],\n", "# 'model': 'Qwen2.5-VL-72B-Instruct',\n", "# 'model_caption_response': '\\n" ] }, { "cell_type": "code", "execution_count": 51, "id": "4235591f", "metadata": {}, "outputs": [], "source": [ "caption_template = '''Question: {Question}\\nYou are tasked with analyzing an image/video to generate a detailed description to help you answer the question. First analyze the image/video and produce a self-contained description—detailed enough that can lead to the correct answer. Wrap the entire description in tags.\\n Next, engage in an internal dialogue and include self-reflection or verification in your reasoning process. Provide your detailed, step-by-step reasoning based on the image/video description information and image/video, and enclose this part within tags.\\n Finally, provide a single word or phrase answer to the question in \\\\boxed{}.\\nThe output format should be: image/video description here reasoning process here \\\\boxed{FINAL ANSWER here}.'''\n", "cot_template = '''Question: {Question}\\nYou FIRST think about the reasoning process as an internal monologue and then provide the final answer. The reasoning process MUST BE enclosed within tags. The final answer MUST BE put in \\\\boxed{}.'''\n", "caption_reasoner_template = '''Text description: {Description}\\nQuestion: {Question}\\nYou are provided a text description of a problem and a question. Determine the answer to the question based on the text description. First provide an internal step-by-step reasoning within tags, then provide a single word or phrase answer in \\\\boxed{}.'''\n" ] }, { "cell_type": "code", "execution_count": 54, "id": "41e6dc51", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 62126/62126 [54:42<00:00, 18.93it/s] \n" ] }, { "data": { "text/plain": [ "9642" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from tqdm import tqdm\n", "\n", "count, caption_answers, caption_reasoners, cot_answers = 0, [], [], []\n", "for i in tqdm(range(len(caption_ans))):\n", " # print(caption_ans[i])\n", " problem = caption_ans[i]['problem']\n", " solution = caption_ans[i]['solution']\n", " prediction_answer = caption_ans[i]['predictions'][0]\n", " caption = extract_description(prediction_answer)\n", " \n", " if caption is not None:\n", " caption_answer = caption_ans[i]['model_caption_response']\n", " accuracy = accuracy_reward(prediction_answer, solution)\n", " accuracy1 = accuracy_reward(caption_answer, solution)\n", " data_index = caption_ans[i]['index']\n", " \n", " \n", " if accuracy == 1 and accuracy1 == 1:\n", " # print(caption_ans[i])\n", " # show_image_any(subset_data['train'][i]['images'])\n", " # break\n", " try:\n", " save_image(subset_data['train'][i]['images'], './cold_start', f'{data_index}.jpg')\n", " cap_ans = {\n", " \"messages\": [\n", " {\n", " \"content\": caption_template.replace('{Question}', problem),\n", " \"role\": \"user\"\n", " },\n", " {\n", " \"content\": prediction_answer,\n", " \"role\": \"assistant\"\n", " }\n", " ],\n", " \"images\": [\n", " f\"cold_start/{data_index}.jpg\"\n", " ]\n", " }\n", " \n", " cap_rea = {\n", " \"messages\": [\n", " {\n", " \"content\": caption_reasoner_template.replace('{Description}', caption).replace('{Question}', problem),\n", " \"role\": \"user\"\n", " },\n", " {\n", " \"content\": caption_answer,\n", " \"role\": \"assistant\"\n", " }\n", " ],\n", " \"images\": [\n", " f\"cold_start/{data_index}.jpg\"\n", " ]\n", " }\n", " \n", " cot_ans = {\n", " \"messages\": [\n", " {\n", " \"content\": cot_template.replace('{Question}', problem),\n", " \"role\": \"user\"\n", " },\n", " {\n", " \"content\": prediction_answer.replace(caption, ''),\n", " \"role\": \"assistant\"\n", " }\n", " ],\n", " \"images\": [\n", " f\"cold_start/{data_index}.jpg\"\n", " ]\n", " }\n", " \n", " # caption_answers, caption_reasoners, cot_answers\n", " caption_answers.append(cap_ans)\n", " caption_reasoners.append(cap_rea)\n", " cot_answers.append(cot_ans)\n", " \n", " count += 1\n", " except:\n", " pass\n", " \n", "count" ] }, { "cell_type": "code", "execution_count": 84, "id": "14ff2bbe", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "9642\n", "9642\n", "9642\n" ] } ], "source": [ "print(len(cot_answers))\n", "print(len(caption_answers))\n", "print(len(caption_reasoners))" ] }, { "cell_type": "code", "execution_count": 81, "id": "8168f20f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'Text description: The image contains four plots arranged in a 2x2 grid. The top two plots show scatter plots of ρ_nn versus some variable, likely energy, but not explicitly labeled. The bottom two plots show histograms of W versus E, where W is likely a probability or weight, and E is energy. Both bottom plots also have a red solid line and a green dashed line, which are likely theoretical fits. The x-axis (E) of the bottom left plot ranges from -10 to 5, while the x-axis of the bottom right plot ranges from -15 to 5. The y-axis (W) is logarithmic in both bottom plots, ranging from 10^-5 to 1. The black histogram in the bottom left plot peaks around E = -4, while the black histogram in the bottom right plot peaks around E = -5. The histogram on the right appears to have a wider spread than the histogram on the left. The red and green lines are different, suggesting different theoretical models.\\nQuestion: Comparing the two W versus E plots at the bottom, what can be inferred about their systems? Options:\\nA. Both systems have the same average energy.\\nB. The system on the right has a wider distribution of energy states.\\nC. The system on the left is more likely to be found in a high-energy state than the one on the right.\\nD. The systems are identical in terms of energy distribution.\\n-\\nYou are provided a text description of a problem and a question. Determine the answer to the question based on the text description. First provide an internal step-by-step reasoning within tags, then provide a single word or phrase answer in \\\\boxed{}.',\n", " 'role': 'user'},\n", " {'content': \"\\nTo determine the correct inference about the systems represented by the two W versus E plots at the bottom, let's analyze the given information:\\n\\n1. **Energy Ranges**: \\n - Bottom left plot: E ranges from -10 to 5.\\n - Bottom right plot: E ranges from -15 to 5.\\n\\n2. **Histogram Peaks**:\\n - Bottom left plot: Peaks around E = -4.\\n - Bottom right plot: Peaks around E = -5.\\n\\n3. **Spread of Histograms**:\\n - The histogram on the right has a wider spread compared to the histogram on the left.\\n\\n4. **Logarithmic Y-Axis**:\\n - Both plots use a logarithmic scale for W, ranging from 10^-5 to 1.\\n\\nGiven these points:\\n\\n- Option A suggests that both systems have the same average energy. However, the peaks at different E values (-4 vs. -5) indicate different average energies.\\n- Option B states that the system on the right has a wider distribution of energy states. This aligns with the observation that the histogram on the right is wider.\\n- Option C implies that the system on the left is more likely to be found in a high-energy state. Since the peak of the left histogram is slightly higher in energy compared to the right, this could be plausible, but it doesn't directly address the spread of the distribution.\\n- Option D claims the systems are identical in terms of energy distribution. This is contradicted by the differences in peak positions and spread.\\n\\nConsidering all observations, the most accurate inference is related to the spread of the energy distributions.\\n\\n\\\\boxed{B}\",\n", " 'role': 'assistant'}],\n", " 'images': ['cold_start/2715.jpg']}" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_reasoners[400]" ] }, { "cell_type": "code", "execution_count": 83, "id": "e0b9854e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'Question: What type of environment does the figure suggest the robot experiments were conducted in? Options:\\nA. An outdoor terrain with varying elevation\\nB. A structured indoor environment with distinct zones\\nC. A virtual simulation environment with artificial obstacles\\nD. An aquatic environment designed for underwater robotics\\nYou FIRST think about the reasoning process as an internal monologue and then provide the final answer. The reasoning process MUST BE enclosed within tags. The final answer MUST BE put in \\\\boxed{}.',\n", " 'role': 'user'},\n", " {'content': '\\nThe image shows a map-like representation of the environment. The colored line indicates the path of the robot. The environment looks like a hallway with rooms branching off. The text mentions \"room laboratory setting\". This suggests a structured indoor environment. Therefore, the answer is B.\\n\\n\\\\boxed{B}',\n", " 'role': 'assistant'}],\n", " 'images': ['cold_start/6717.jpg']}" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cot_answers[1000]" ] }, { "cell_type": "code", "execution_count": 85, "id": "03e454e3", "metadata": {}, "outputs": [], "source": [ "def strip_before_think(text: str) -> str:\n", " \"\"\"Return the substring starting from the first '' tag.\"\"\"\n", " i = text.find(\"\")\n", " return text[i:] if i != -1 else text \n", "\n", "\n", "new_cot_answers = []\n", "\n", "for ele in cot_answers:\n", " ele['messages'][1]['content'] = strip_before_think(ele['messages'][1]['content'])\n", " new_cot_answers.append(ele)" ] }, { "cell_type": "code", "execution_count": 89, "id": "a1e1b552", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'Question: What does the DFA in the graph most likely stand for? Options:\\nA) Deterministic Finite Automaton\\nB) Detrended Fluctuation Analysis\\nC) Differential Functional Analysis\\nD) Dynamic Fourier Analysis\\nYou FIRST think about the reasoning process as an internal monologue and then provide the final answer. The reasoning process MUST BE enclosed within tags. The final answer MUST BE put in \\\\boxed{}.',\n", " 'role': 'user'},\n", " {'content': 'The graph shows data related to \"DFA air humidity\" and \"DFA air temperature\". The y-axis label includes \"FDFA(n)\". This suggests that DFA is a method or analysis applied to air humidity and air temperature data. Looking at the options, \"Detrended Fluctuation Analysis\" (B) is a statistical method often used to analyze time series data for long-range correlations. This seems like a plausible explanation for DFA. The other options, \"Deterministic Finite Automaton\" (A), \"Differential Functional Analysis\" (C), and \"Dynamic Fourier Analysis\" (D), don\\'t seem as relevant in the context of analyzing air humidity and temperature data. Therefore, the most likely meaning of DFA in this context is Detrended Fluctuation Analysis.\\n\\n\\\\boxed{B}',\n", " 'role': 'assistant'}],\n", " 'images': ['cold_start/3935.jpg']}" ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_cot_answers[600]" ] }, { "cell_type": "code", "execution_count": null, "id": "6903bf49", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1\n", "{'messages': [{'content': 'Question: What is the impact of the SD_max parameter on the cumulative economic cost in a given strategy? Options:\\nA) SD_max has no impact on the cumulative economic cost.\\nB) A higher SD_max leads to a higher cumulative economic cost.\\nC) A lower SD_max leads to a higher cumulative economic cost.\\nD) SD_max inversely correlates with the number of weeks.\\nYou FIRST think about the reasoning process as an internal monologue and then provide the final answer. The reasoning process MUST BE enclosed within tags. The final answer MUST BE put in \\\\boxed{}.', 'role': 'user'}, {'content': '\\nBased on the image description, a higher SD_max leads to a higher cumulative economic cost, especially for the \"FIXED\" strategy.\\n \\\\boxed{B}', 'role': 'assistant'}], 'images': ['cold_start/1396.jpg']}\n" ] } ], "source": [ "counts = 0\n", "for ele in new_cot_answers:\n", " if ele['messages'][1]['content'].startswith('') == False:\n", " print('1')\n", " print(ele)\n", " break" ] }, { "cell_type": "code", "execution_count": 101, "id": "842593b8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1\n", "{'messages': [{'content': 'Question: What is the relationship between θ and t as shown in both graphs (a) and (b)? Options:\\nA. θ increases as t increases.\\nB. θ remains constant as t increases.\\nC. θ decreases as t increases.\\nD. θ first increases and then decreases as t increases.\\n## Question 2\\nYou are tasked with analyzing an image/video to generate a detailed description to help you answer the question. First analyze the image/video and produce a self-contained description—detailed enough that can lead to the correct answer. Wrap the entire description in tags.\\n Next, engage in an internal dialogue and include self-reflection or verification in your reasoning process. Provide your detailed, step-by-step reasoning based on the image/video description information and image/video, and enclose this part within tags.\\n Finally, provide a single word or phrase answer to the question in \\\\boxed{}.\\nThe output format should be: image/video description here reasoning process here \\\\boxed{FINAL ANSWER here}.', 'role': 'user'}, {'content': ' is based on the image.\\n \\n \\n The image contains two graphs, (a) and (b), both plotting θ (theta) on the y-axis (logarithmic scale) against t (time) on the x-axis. Graph (a) shows two curves, one black and one red, representing data for \"512\" and \"1024\" respectively. Graph (b) also shows two curves, one black and one red, representing data for \"96\" and \"192\" respectively. In both graphs, as t increases, θ decreases. Both graphs also contain insets. The inset in graph (a) shows a zoomed-in view of the initial part of the curves, and the inset in graph (b) shows a plot of θ_in versus L, which appears to be a linear relationship.\\n \\n \\n The question asks about the relationship between θ and t in both graphs (a) and (b).\\n By observing the graphs, it\\'s clear that as the value of t (time) increases along the x-axis, the value of θ (theta) decreases along the y-axis. The y-axis is on a logarithmic scale, but the trend is still clearly decreasing. Therefore, the correct answer is that θ decreases as t increases.\\n \\n \\\\boxed{C}', 'role': 'assistant'}], 'images': ['cold_start/90.jpg']}\n" ] } ], "source": [ "for ele in caption_answers:\n", " if ele['messages'][1]['content'].startswith('') == False:\n", " print('1')\n", " print(ele)\n", " break" ] }, { "cell_type": "code", "execution_count": 121, "id": "7f756700", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 9642/9642 [00:00<00:00, 291787.67it/s]\n" ] }, { "data": { "text/plain": [ "9364" ] }, "execution_count": 121, "metadata": {}, "output_type": "execute_result" } ], "source": [ "counts = 0\n", "final_cot_answers, final_caption_reasoners, final_caption_answers = [], [], []\n", "for i in tqdm(range(len(new_cot_answers))):\n", " # print(new_cot_answers[i]['messages'][1]['content'].startswith(''))\n", " # print(caption_reasoners[i]['messages'][1]['content'].startswith(''))\n", " # print(caption_answers[i]['messages'][1]['content'].startswith(''))\n", " \n", " ii = new_cot_answers[i]['messages'][1]['content'].startswith('')\n", " iii = caption_reasoners[i]['messages'][1]['content'].startswith('')\n", " iiii = caption_answers[i]['messages'][1]['content'].startswith('')\n", " if ii == True and iii == True and iiii == True:\n", " counts += 1\n", " # print('-'*10)\n", " # if new_cot_answers[i]['messages'][1]['content'].startswith('') == True \\\n", " # and caption_reasoners[i]['messages'][1]['content'].startswith('') == True\\\n", " # and caption_answers[i]['messages'][1]['content'].startswith('') == True:\n", " \n", " # count += 1\n", " final_cot_answers.append(new_cot_answers[i])\n", " final_caption_reasoners.append(caption_reasoners[i])\n", " final_caption_answers.append(caption_answers[i])\n", " \n", "counts" ] }, { "cell_type": "code", "execution_count": 122, "id": "cf3e4378", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "9364\n", "9364\n", "9364\n" ] } ], "source": [ "print(len(final_caption_answers))\n", "print(len(final_caption_reasoners))\n", "print(len(final_cot_answers))" ] }, { "cell_type": "code", "execution_count": 23, "id": "909450de", "metadata": {}, "outputs": [], "source": [ "import json\n", "from pathlib import Path\n", "from typing import List, Dict, Any, Union\n", "\n", "def write_jsonl(\n", " data: List[Dict[str, Any]],\n", " outfile: Union[str, Path],\n", " *,\n", " newline_delimited: bool = False,\n", " indent: int | None = 2,\n", " ensure_ascii: bool = False,\n", ") -> Path:\n", " \"\"\"\n", " Save a list of dictionaries to `outfile` as JSON.\n", "\n", " Parameters\n", " ----------\n", " data : list of dicts to write.\n", " outfile : target path (created if parent folders don’t exist).\n", " newline_delimited : if True, write one JSON object per line (JSONL);\n", " if False, write a single pretty-printed list.\n", " indent : `None` for compact; an int for pretty-print spacing.\n", " Ignored when `newline_delimited=True`.\n", " ensure_ascii : keep non-ASCII chars escaped (default False).\n", "\n", " Returns\n", " -------\n", " Path to the written file.\n", " \"\"\"\n", " outfile = Path(outfile)\n", " outfile.parent.mkdir(parents=True, exist_ok=True)\n", "\n", " with outfile.open(\"w\", encoding=\"utf-8\") as f:\n", " if newline_delimited:\n", " for obj in data:\n", " json.dump(obj, f, ensure_ascii=ensure_ascii)\n", " f.write(\"\\n\")\n", " else:\n", " json.dump(data, f, indent=indent, ensure_ascii=ensure_ascii)\n", "\n", " return outfile\n", "\n", "# write_jsonl(final_caption_answers, \"./sft/vision_see_think.json\")\n", "# write_jsonl(final_caption_reasoners, \"./sft/caption_reasoners(text).json\")\n", "# write_jsonl(final_cot_answers, \"./sft/vision_reasoner.json\")" ] }, { "cell_type": "code", "execution_count": 108, "id": "234d593d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_cot_answers[0]['messages'][1]['content'].startswith('')" ] }, { "cell_type": "code", "execution_count": 109, "id": "a1de44b7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_reasoners[0]['messages'][1]['content'].startswith('')" ] }, { "cell_type": "code", "execution_count": 112, "id": "355bdccb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_answers[0]['messages'][1]['content'].startswith('')" ] }, { "cell_type": "code", "execution_count": 1, "id": "44f347c3", "metadata": {}, "outputs": [], "source": [ "import json\n", "from pathlib import Path\n", "from typing import List, Dict, Any, Union\n", "\n", "def load_json_records(\n", " infile: Union[str, Path],\n", " *,\n", " newline_delimited: bool | None = None,\n", ") -> List[Dict[str, Any]]:\n", " \"\"\"\n", " Read a JSON (or JSONL) file into a list of dicts.\n", "\n", " Parameters\n", " ----------\n", " infile : Path to the file to read.\n", " newline_delimited : • True – treat file as JSONL (one JSON object per line)\n", " • False – treat file as a single JSON array\n", " • None – auto-detect by peeking at the first non-blank char\n", " ('[' ⇒ array JSON, otherwise JSONL)\n", "\n", " Returns\n", " -------\n", " List[Dict[str, Any]]\n", " \"\"\"\n", " infile = Path(infile)\n", "\n", " if newline_delimited is None:\n", " # Peek at the first non-whitespace character\n", " with infile.open(\"r\", encoding=\"utf-8\") as f:\n", " for ch in iter(lambda: f.read(1), \"\"):\n", " if not ch.isspace():\n", " newline_delimited = (ch != \"[\")\n", " break\n", " else: # empty file\n", " return []\n", "\n", " with infile.open(\"r\", encoding=\"utf-8\") as f:\n", " if newline_delimited:\n", " return [json.loads(line) for line in f if line.strip()]\n", " else:\n", " return json.load(f)" ] }, { "cell_type": "code", "execution_count": 18, "id": "3b34a284", "metadata": {}, "outputs": [], "source": [ "# description_answers = load_json_records('../LLaMA-Factory/data/vision_reasoner.json')\n", "# cot_answers = load_json_records('../LLaMA-Factory/data/vision_see_think.json')\n", "caption_reasoners = load_json_records('../LLaMA-Factory/data/caption_reasoners(text).json')" ] }, { "cell_type": "code", "execution_count": 19, "id": "53d8442d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'Question: Based on the distribution of data points in the graph, what can be inferred about the relationship between the variables plotted on the x and y axes? Options:\\nA. The variables are directly proportional.\\nB. The variables are inversely proportional.\\nC. The variables follow a power-law distribution.\\nD. The variables are unrelated.\\n-\\nYou FIRST think about the reasoning process as an internal monologue and then provide the final answer. The reasoning process MUST BE enclosed within tags. The final answer MUST BE put in \\\\boxed{}.',\n", " 'role': 'user'},\n", " {'content': 'The question asks about the relationship between the variables plotted on the x and y axes. The graph is a log-log plot, and the data points form straight lines. This indicates a power-law relationship. The options are:\\nA. The variables are directly proportional. This would be a straight line on a linear plot, not necessarily on a log-log plot.\\nB. The variables are inversely proportional. This is a specific type of power-law relationship (with an exponent of -1).\\nC. The variables follow a power-law distribution. This is consistent with the straight lines on the log-log plot.\\nD. The variables are unrelated. This is not consistent with the clear patterns in the data.\\n\\nSince the lines are straight on a log-log plot, the relationship is a power law. Option C is the most general and accurate description of the relationship.\\n\\n\\\\boxed{C}',\n", " 'role': 'assistant'}],\n", " 'images': ['cold_start/7.jpg']}" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "description_answers[0]" ] }, { "cell_type": "code", "execution_count": 6, "id": "dcabaa9e", "metadata": {}, "outputs": [], "source": [ "def count_image_tags(text: str) -> int:\n", " \"\"\"Return how many times the literal '' appears in the string.\"\"\"\n", " return text.count(\"\")" ] }, { "cell_type": "code", "execution_count": 16, "id": "9faa2639", "metadata": {}, "outputs": [], "source": [ "for ele in description_answers:\n", "# for ele in cot_answers:\n", " qs = ele['messages'][0]['content']\n", " num_tags = count_image_tags(qs)\n", " img_len = len(ele['images'])\n", " if num_tags !=1 and img_len != 1:\n", " print(num_tags)" ] }, { "cell_type": "code", "execution_count": 21, "id": "e1e089db", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'messages': [{'content': 'Text description: The image is a log-log plot showing the relationship between two variables, denoted as Delta on the x-axis and another variable on the y-axis. The y-axis ranges from 10^1 to 10^6, and the x-axis ranges from 1 to 100. There are two distinct sets of data points plotted on the graph, represented by circles and squares, and triangles. The circles and squares appear to follow a power-law relationship with an exponent of approximately -3, as indicated by the label \"Delta^-3\" near the data. The triangles appear to follow a power-law relationship with an exponent of approximately -2, as indicated by the label \"Delta^-2\" near the data. The lines are straight on the log-log plot, which is characteristic of power-law relationships.\\nQuestion: Based on the distribution of data points in the graph, what can be inferred about the relationship between the variables plotted on the x and y axes? Options:\\nA. The variables are directly proportional.\\nB. The variables are inversely proportional.\\nC. The variables follow a power-law distribution.\\nD. The variables are unrelated.\\n-\\nYou are provided a text description of a problem and a question. Determine the answer to the question based on the text description. First provide an internal step-by-step reasoning within tags, then provide a single word or phrase answer in \\\\boxed{}.',\n", " 'role': 'user'},\n", " {'content': '\\nThe description indicates that the graph is a log-log plot, which is used to identify power-law relationships. The data points for both sets (circles and squares, and triangles) form straight lines on this plot, which is a characteristic feature of power-law distributions. Additionally, the labels \"Delta^-3\" and \"Delta^-2\" suggest specific power-law exponents for each set of data points. This implies that the relationship between the variables on the x-axis (Delta) and the y-axis follows a power-law distribution rather than being directly proportional, inversely proportional, or unrelated.\\n\\nStep 1: Identify the type of plot - Log-log plot suggests looking for power-law relationships.\\nStep 2: Analyze the shape of the data - Straight lines on a log-log plot indicate power-law relationships.\\nStep 3: Consider the given labels - \"Delta^-3\" and \"Delta^-2\" confirm power-law relationships with specific exponents.\\nStep 4: Eliminate incorrect options - Directly proportional, inversely proportional, and unrelated do not fit the described characteristics.\\n\\nTherefore, the correct inference is that the variables follow a power-law distribution.\\n\\n\\\\boxed{C}',\n", " 'role': 'assistant'}],\n", " 'images': ['cold_start/7.jpg']}" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "caption_reasoners[0]" ] }, { "cell_type": "code", "execution_count": 22, "id": "2ea93a87", "metadata": {}, "outputs": [], "source": [ "new_caption_reasoners = []\n", "\n", "for ele in caption_reasoners:\n", " result = {\n", " \"instruction\": ele['messages'][0]['content'],\n", " \"input\": \"\",\n", " \"output\": ele['messages'][1]['content']\n", " }\n", " \n", " new_caption_reasoners.append(result)" ] }, { "cell_type": "code", "execution_count": 24, "id": "9de2c700", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "PosixPath('../LLaMA-Factory/data/caption_reasoners(text).json')" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "write_jsonl(new_caption_reasoners, \"../LLaMA-Factory/data/caption_reasoners(text).json\")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 }