{"action":"created","issue":{"url":"https://api.github.com/repos/google/seq2seq/issues/205","repository_url":"https://api.github.com/repos/google/seq2seq","labels_url":"https://api.github.com/repos/google/seq2seq/issues/205/labels{/name}","comments_url":"https://api.github.com/repos/google/seq2seq/issues/205/comments","events_url":"https://api.github.com/repos/google/seq2seq/issues/205/events","html_url":"https://github.com/google/seq2seq/issues/205","id":226194775,"number":205,"title":"trying to follow the nmt tutorial, cannot run the training step","user":{"login":"KyonP","id":6139342,"avatar_url":"https://avatars0.githubusercontent.com/u/6139342?v=3","gravatar_id":"","url":"https://api.github.com/users/KyonP","html_url":"https://github.com/KyonP","followers_url":"https://api.github.com/users/KyonP/followers","following_url":"https://api.github.com/users/KyonP/following{/other_user}","gists_url":"https://api.github.com/users/KyonP/gists{/gist_id}","starred_url":"https://api.github.com/users/KyonP/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/KyonP/subscriptions","organizations_url":"https://api.github.com/users/KyonP/orgs","repos_url":"https://api.github.com/users/KyonP/repos","events_url":"https://api.github.com/users/KyonP/events{/privacy}","received_events_url":"https://api.github.com/users/KyonP/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":4,"created_at":"2017-05-04T07:10:46Z","updated_at":"2017-05-08T08:28:59Z","closed_at":null,"body":"I'm following the tutorial (https://google.github.io/seq2seq/nmt/), but can't run the code.\r\n\r\nActually, I'm not understanding the code explained in the tutorial. Do I have to type all those arguments in the command line?\r\n\r\nI've set environment variables, and then copy-and-pasted the code in Training step.\r\n\r\nAnd I got following lousy error. \r\n\r\n\r\n\r\n~/reference_code/seq2seq#` python -m bin.train \\\r\n>   --config_paths=\"\r\n>       ./example_configs/nmt_small.yml,\r\n>       ./example_configs/train_seq2seq.yml,\r\n>       ./example_configs/text_metrics_bpe.yml\" \\\r\n>   --model_params \"\r\n>       vocab_source: $VOCAB_SOURCE\r\n>       vocab_target: $VOCAB_TARGET\" \\\r\n>   --input_pipeline_train \"\r\n>     class: ParallelTextInputPipeline\r\n>     params:\r\n>       source_files:\r\n>         - $TRAIN_SOURCES\r\n>       target_files:\r\n>         - $TRAIN_TARGETS\" \\\r\n>   --input_pipeline_dev \"\r\n>     class: ParallelTextInputPipeline\r\n>     params:\r\n>        source_files:\r\n>         - $DEV_SOURCES\r\n>        target_files:\r\n>         - $DEV_TARGETS\" \\\r\n>   --batch_size 32 \\\r\n>   --train_steps 10000 \\\r\n>   --output_dir $MODEL_DIR\r\nINFO:tensorflow:Loading config from /root/vchatbot/reference_code/seq2seq/example_configs/nmt_small.yml\r\nINFO:tensorflow:Loading config from /root/vchatbot/reference_code/seq2seq/example_configs/train_seq2seq.yml\r\nINFO:tensorflow:Loading config from /root/vchatbot/reference_code/seq2seq/example_configs/text_metrics_bpe.yml\r\nINFO:tensorflow:Final Config:\r\nbuckets: 10,20,30,40\r\ndefault_params:\r\n- {separator: ' '}\r\n- {postproc_fn: seq2seq.data.postproc.strip_bpe}\r\nhooks:\r\n- {class: PrintModelAnalysisHook}\r\n- {class: MetadataCaptureHook}\r\n- {class: SyncReplicasOptimizerHook}\r\n- class: TrainSampleHook\r\n  params: {every_n_steps: 1000}\r\nmetrics:\r\n- {class: LogPerplexityMetricSpec}\r\n- class: BleuMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_1/f_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_1/r_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_1/p_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_2/f_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_2/r_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_2/p_score,\r\n    separator: ' '}\r\n- class: RougeMetricSpec\r\n  params: {postproc_fn: seq2seq.data.postproc.strip_bpe, rouge_type: rouge_l/f_score,\r\n    separator: ' '}\r\nmodel: AttentionSeq2Seq\r\nmodel_params:\r\n  attention.class: seq2seq.decoders.attention.AttentionLayerDot\r\n  attention.params: {num_units: 128}\r\n  bridge.class: seq2seq.models.bridges.ZeroBridge\r\n  decoder.class: seq2seq.decoders.AttentionDecoder\r\n  decoder.params:\r\n    rnn_cell:\r\n      cell_class: GRUCell\r\n      cell_params: {num_units: 128}\r\n      dropout_input_keep_prob: 0.8\r\n      dropout_output_keep_prob: 1.0\r\n      num_layers: 1\r\n  embedding.dim: 128\r\n  encoder.class: seq2seq.encoders.BidirectionalRNNEncoder\r\n  encoder.params:\r\n    rnn_cell:\r\n      cell_class: GRUCell\r\n      cell_params: {num_units: 128}\r\n      dropout_input_keep_prob: 0.8\r\n      dropout_output_keep_prob: 1.0\r\n      num_layers: 1\r\n  optimizer.learning_rate: 0.0001\r\n  optimizer.name: Adam\r\n  optimizer.params: {epsilon: 8.0e-07}\r\n  source.max_seq_len: 50\r\n  source.reverse: false\r\n  target.max_seq_len: 50\r\n\r\nWARNING:tensorflow:Ignoring config flag: default_params\r\nINFO:tensorflow:Setting save_checkpoints_secs to 600\r\nINFO:tensorflow:Creating ParallelTextInputPipeline in mode=train\r\nINFO:tensorflow:\r\nParallelTextInputPipeline:\r\n  !!python/unicode 'num_epochs': null\r\n  !!python/unicode 'shuffle': true\r\n  !!python/unicode 'source_delimiter': !!python/unicode ' '\r\n  !!python/unicode 'source_files': [null]\r\n  !!python/unicode 'target_delimiter': !!python/unicode ' '\r\n  !!python/unicode 'target_files': [null]\r\n\r\nINFO:tensorflow:Creating ParallelTextInputPipeline in mode=eval\r\nINFO:tensorflow:\r\nParallelTextInputPipeline:\r\n  !!python/unicode 'num_epochs': 1\r\n  !!python/unicode 'shuffle': false\r\n  !!python/unicode 'source_delimiter': !!python/unicode ' '\r\n  !!python/unicode 'source_files': [null]\r\n  !!python/unicode 'target_delimiter': !!python/unicode ' '\r\n  !!python/unicode 'target_files': [null]\r\n\r\nINFO:tensorflow:Using config: {'_model_dir': None, '_save_checkpoints_secs': 600, '_num_ps_replicas': 0, '_keep_checkpoint_max': 5, '_tf_random_seed': None, '_task_type': None, '_environment': 'local', '_is_chief': True, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f9fcaef7cd0>, '_tf_config': gpu_options {\r\n  per_process_gpu_memory_fraction: 1.0\r\n}\r\n, '_num_worker_replicas': 0, '_task_id': 0, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_evaluation_master': '', '_keep_checkpoint_every_n_hours': 4, '_master': ''}\r\nINFO:tensorflow:Creating PrintModelAnalysisHook in mode=train\r\nINFO:tensorflow:\r\nPrintModelAnalysisHook: {}\r\n\r\nINFO:tensorflow:Creating MetadataCaptureHook in mode=train\r\nINFO:tensorflow:\r\nMetadataCaptureHook: {!!python/unicode 'step': 10}\r\n\r\nINFO:tensorflow:Creating SyncReplicasOptimizerHook in mode=train\r\nINFO:tensorflow:\r\nSyncReplicasOptimizerHook: {}\r\n\r\nINFO:tensorflow:Creating TrainSampleHook in mode=train\r\nINFO:tensorflow:\r\nTrainSampleHook: {!!python/unicode 'every_n_secs': null, !!python/unicode 'every_n_steps': 1000,\r\n  !!python/unicode 'source_delimiter': !!python/unicode ' ', !!python/unicode 'target_delimiter': !!python/unicode ' '}\r\n\r\nINFO:tensorflow:Creating LogPerplexityMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nLogPerplexityMetricSpec: {}\r\n\r\nINFO:tensorflow:Creating BleuMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nBleuMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'separator': !!python/unicode ' ', !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_1/f_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_1/r_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_1/p_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_2/f_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_2/r_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_2/p_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Creating RougeMetricSpec in mode=eval\r\nINFO:tensorflow:\r\nRougeMetricSpec: {!!python/unicode 'eos_token': !!python/unicode 'SEQUENCE_END', !!python/unicode 'postproc_fn': !!python/unicode 'seq2seq.data.postproc.strip_bpe',\r\n  !!python/unicode 'rouge_type': !!python/unicode 'rouge_l/f_score', !!python/unicode 'separator': !!python/unicode ' ',\r\n  !!python/unicode 'sos_token': !!python/unicode 'SEQUENCE_START'}\r\n\r\nINFO:tensorflow:Training model for 1000 steps\r\nTraceback (most recent call last):\r\n  File \"/usr/lib/python2.7/runpy.py\", line 162, in _run_module_as_main\r\n    \"__main__\", fname, loader, pkg_name)\r\n  File \"/usr/lib/python2.7/runpy.py\", line 72, in _run_code\r\n    exec code in run_globals\r\n  File \"/root/vchatbot/reference_code/seq2seq/bin/train.py\", line 277, in <module>\r\n    tf.app.run()\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py\", line 48, in run\r\n    _sys.exit(main(_sys.argv[:1] + flags_passthrough))\r\n  File \"/root/vchatbot/reference_code/seq2seq/bin/train.py\", line 272, in main\r\n    schedule=FLAGS.schedule)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/learn_runner.py\", line 111, in run\r\n    return _execute_schedule(experiment, schedule)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/learn_runner.py\", line 46, in _execute_schedule\r\n    return task()\r\n  File \"seq2seq/contrib/experiment.py\", line 104, in continuous_train_and_eval\r\n    monitors=self._train_monitors)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/deprecation.py\", line 281, in new_func\r\n    return func(*args, **kwargs)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py\", line 430, in fit\r\n    loss = self._train_model(input_fn=input_fn, hooks=hooks)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py\", line 925, in _train_model\r\n    features, labels = input_fn()\r\n  File \"seq2seq/training/utils.py\", line 260, in input_fn\r\n    data_provider = pipeline.make_data_provider()\r\n  File \"seq2seq/data/input_pipeline.py\", line 180, in make_data_provider\r\n    **kwargs)\r\n  File \"seq2seq/data/parallel_data_provider.py\", line 125, in __init__\r\n    seed=seed)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/data/parallel_reader.py\", line 210, in parallel_read\r\n    data_files = get_data_files(data_sources)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/data/parallel_reader.py\", line 276, in get_data_files\r\n    data_files += get_data_files(source)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/data/parallel_reader.py\", line 278, in get_data_files\r\n    if '*' in data_sources or '?' in data_sources or '[' in data_sources:\r\nTypeError: argument of type 'NoneType' is not iterable\r\n\r\n\r\n\r\n\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/google/seq2seq/issues/comments/299805283","html_url":"https://github.com/google/seq2seq/issues/205#issuecomment-299805283","issue_url":"https://api.github.com/repos/google/seq2seq/issues/205","id":299805283,"user":{"login":"KyonP","id":6139342,"avatar_url":"https://avatars0.githubusercontent.com/u/6139342?v=3","gravatar_id":"","url":"https://api.github.com/users/KyonP","html_url":"https://github.com/KyonP","followers_url":"https://api.github.com/users/KyonP/followers","following_url":"https://api.github.com/users/KyonP/following{/other_user}","gists_url":"https://api.github.com/users/KyonP/gists{/gist_id}","starred_url":"https://api.github.com/users/KyonP/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/KyonP/subscriptions","organizations_url":"https://api.github.com/users/KyonP/orgs","repos_url":"https://api.github.com/users/KyonP/repos","events_url":"https://api.github.com/users/KyonP/events{/privacy}","received_events_url":"https://api.github.com/users/KyonP/received_events","type":"User","site_admin":false},"created_at":"2017-05-08T08:28:59Z","updated_at":"2017-05-08T08:28:59Z","body":"Still suffering. Anyone else has this issue?"}}
{"actor":{"display_login":"KyonP"}}