Training Error

[srtarun]

I had the following error while trying to run the following command "sh train.sh data/monument_300 120000"

output:

Job id 0
Loading hparams from ../data/monument_300_model/hparams
Updating hparams.test_prefix: None -> ../data/monument_300/test
Updating hparams.num_train_steps: 12000 -> 120000
  saving hparams to ../data/monument_300_model/hparams
  saving hparams to ../data/monument_300_model/best_bleu/hparams
  attention=
  attention_architecture=standard
  batch_size=128
  beam_width=0
  best_bleu=0
  best_bleu_dir=../data/monument_300_model/best_bleu
  bpe_delimiter=None
  colocate_gradients_with_ops=True
  decay_factor=0.98
  decay_steps=10000
  dev_prefix=../data/monument_300/dev
  dropout=0.2
  encoder_type=uni
  eos=</s>
  epoch_step=0
  forget_bias=1.0
  infer_batch_size=32
  init_op=uniform
  init_weight=0.1
  learning_rate=1.0
  length_penalty_weight=0.0
  log_device_placement=False
  max_gradient_norm=5.0
  max_train=0
  metrics=[u'bleu']
  num_buckets=5
  num_embeddings_partitions=0
  num_gpus=1
  num_layers=2
  num_residual_layers=0
  num_train_steps=120000
  num_units=128
  optimizer=sgd
  out_dir=../data/monument_300_model
  pass_hidden_state=True
  random_seed=None
  residual=False
  share_vocab=False
  sos=<s>
  source_reverse=False
  src=en
  src_max_len=50
  src_max_len_infer=None
  src_vocab_file=../data/monument_300_model/vocab.en
  src_vocab_size=2228
  start_decay_step=0
  steps_per_external_eval=None
  steps_per_stats=100
  test_prefix=../data/monument_300/test
  tgt=sparql
  tgt_max_len=50
  tgt_max_len_infer=None
  tgt_vocab_file=../data/monument_300_model/vocab.sparql
  tgt_vocab_size=1763
  time_major=True
  train_prefix=../data/monument_300/train
  unit_type=lstm
  vocab_prefix=../data/monument_300/vocab
Traceback (most recent call last):
  File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 495, in <module>
    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
  File "/home/tarun/.local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 126, in run
    _sys.exit(main(argv))
  File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 488, in main
    run_main(FLAGS, default_hparams, train_fn, inference_fn)
  File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 481, in run_main
    train_fn(hparams, target_session=target_session)
  File "nmt/train.py", line 171, in train
    train_model = model_helper.create_train_model(model_creator, hparams, scope)
  File "nmt/model_helper.py", line 69, in create_train_model
    src_dataset = tf.contrib.data.TextLineDataset(src_file)
AttributeError: 'module' object has no attribute 'TextLineDataset'

[amanmehta-maniac]

The error is unreadable. Is it solved? If not, use pastebin to show your exact error so that I could help you.

Regards, Aman

On Fri, May 4, 2018 at 6:24 PM, S R Tarun notifications@github.com wrote:

I had the following error while trying to run the following command "sh train.sh data/monument_300 120000"

output: Job id 0 Loading hparams from ../data/monument_300_model/hparams Updating hparams.test_prefix: None -> ../data/monument_300/test Updating hparams.num_train_steps: 12000 -> 120000

saving hparams to ../data/monument_300_model/hparams saving hparams to ../data/monument_300_model/best_bleu/hparams attention= attention_architecture=standard batch_size=128 beam_width=0 best_bleu=0 best_bleu_dir=../data/monument_300_model/best_bleu bpe_delimiter=None colocate_gradients_with_ops=True decay_factor=0.98 decay_steps=10000 dev_prefix=../data/monument_300/dev dropout=0.2 encoder_type=uni eos= epoch_step=0 forget_bias=1.0 infer_batch_size=32 init_op=uniform init_weight=0.1 learning_rate=1.0 length_penalty_weight=0.0 log_device_placement=False max_gradient_norm=5.0 max_train=0 metrics=[u'bleu'] num_buckets=5 num_embeddings_partitions=0 num_gpus=1 num_layers=2 num_residual_layers=0 num_train_steps=120000 num_units=128 optimizer=sgd out_dir=../data/monument_300_model pass_hidden_state=True random_seed=None residual=False share_vocab=False sos= source_reverse=False src=en src_max_len=50 src_max_len_infer=None src_vocab_file=../data/monument_300_model/vocab.en src_vocab_size=2228 start_decay_step=0 steps_per_external_eval=None steps_per_stats=100 test_prefix=../data/monument_300/test tgt=sparql tgt_max_len=50 tgt_max_len_infer=None tgt_vocab_file=../data/monument_300_model/vocab.sparql tgt_vocab_size=1763 time_major=True train_prefix=../data/monument_300/train unit_type=lstm vocab_prefix=../data/monument_300/vocab Traceback (most recent call last): File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main "main", fname, loader, pkg_name) File "/usr/lib/python2.7/runpy.py", line 72, in _run_code exec code in run_globals File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 495, in tf.app.run(main=main, argv=[sys.argv[0]] + unparsed) File "/home/tarun/.local/lib/python2.7/site-packages/ tensorflow/python/platform/app.py", line 126, in run _sys.exit(main(argv)) File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 488, in main run_main(FLAGS, default_hparams, train_fn, inference_fn) File "/home/tarun/dbpedia/NSpM/nmt/nmt/nmt.py", line 481, in run_main train_fn(hparams, target_session=target_session) File "nmt/train.py", line 171, in train train_model = model_helper.create_train_model(model_creator, hparams, scope) File "nmt/model_helper.py", line 69, in create_train_model src_dataset = tf.contrib.data.TextLineDataset(src_file) AttributeError: 'module' object has no attribute 'TextLineDataset'

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[edgardmarx]

I think he is referring to the last line.

AttributeError: 'module' object has no attribute 'TextLineDataset'

[amanmehta-maniac]

The error is probably due to different version of tf. The training works fine for me and my tf version is 1.3.0 (for python2). What's yours?

[srtarun]

My version of tf is 1.8.0(python 2). Im not sure if this is the real problem but I think even this is considered as a bug. The model should be compatible for latest versions as well.