The error manifests in multiple ways, always during evaluation and some kind of shape error:

• #102
• #69
• #98
• #101

Possible causes:

• Some kind of bug in tf.learn evaluate that causes issues with the GPU during eva (this doesn't seem to be a problem with CPU training)
• Mismatch of parameters or training data in training/eval
• Issue with the data reading / input pipeline, e.g. mismatched sequence lengths.

It could be related to these Tensorflow issues:

• https://github.com/tensorflow/tensorflow/issues/7015
• https://github.com/tensorflow/tensorflow/issues/6469

For everyone having this issue, please answer the following to help debug:

• What versions of TensorFlow are you using?
• Can you run on the CPU without error?
• What versions of CUDA are you using?

Parsing GraphDef... Parsing RunMetadata... Parsing OpLog... Preparing Views... Traceback (most recent call last): File "/usr/lib64/python2.7/runpy.py", line 162, in _run_module_as_main "main", fname, loader, pkg_name) File "/usr/lib64/python2.7/runpy.py", line 72, in _run_code exec code in run_globals File "/disk1/mouna/code/seq2seq/bin/train.py", line 251, in tf.app.run() File "/usr/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run _sys.exit(main(_sys.argv[:1] + flags_passthrough)) File "/disk1/mouna/code/seq2seq/bin/train.py", line 246, in main schedule=FLAGS.schedule) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/learn_runner.py", line 106, in run return task() File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 459, in train_and_evaluate self.train(delay_secs=0) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 281, in train monitors=self._train_monitors + extra_hooks) File "/usr/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 280, in new_func return func(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 426, in fit loss = self._train_model(input_fn=input_fn, hooks=hooks) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 984, in _train_model _, loss = mon_sess.run([model_fn_ops.train_op, model_fn_ops.loss]) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 462, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 786, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 744, in run return self._sess.run(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 899, in run run_metadata=run_metadata)) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 1157, in after_run induce_stop = m.step_end(self._last_step, result) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 356, in step_end return self.every_n_step_end(step, output) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 657, in every_n_step_end steps=self.eval_steps, metrics=self.metrics, name=self.name) File "/usr/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 280, in new_func return func(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 514, in evaluate log_progress=log_progress) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 836, in _evaluate_model hooks=hooks) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/training/python/training/evaluation.py", line 430, in evaluate_once session.run(eval_ops, feed_dict) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 462, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 786, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 744, in run return self._sess.run(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 891, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 744, in run return self._sess.run(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run run_metadata_ptr) File "/usr/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 965, in _run feed_dict_string, options, run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1015, in _do_run target_list, options, run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1035, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InvalidArgumentError: Tried to read from index 32 but array size is: 32 [[Node: model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3 = TensorArrayReadV3[_class=["loc:@model/att_seq2seq/decode/TrainingHelper/TensorArray"], dtype=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch, model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch_1/_463, model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch_2)]]

Caused by op u'model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3', defined at: File "/usr/lib64/python2.7/runpy.py", line 162, in _run_module_as_main "main", fname, loader, pkg_name) File "/usr/lib64/python2.7/runpy.py", line 72, in _run_code exec code in run_globals File "/disk1/mouna/code/seq2seq/bin/train.py", line 251, in tf.app.run() File "/usr/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run _sys.exit(main(_sys.argv[:1] + flags_passthrough)) File "/disk1/mouna/code/seq2seq/bin/train.py", line 246, in main schedule=FLAGS.schedule) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/learn_runner.py", line 106, in run return task() File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 459, in train_and_evaluate self.train(delay_secs=0) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 281, in train monitors=self._train_monitors + extra_hooks) File "/usr/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 280, in new_func return func(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 426, in fit loss = self._train_model(input_fn=input_fn, hooks=hooks) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 984, in _train_model _, loss = mon_sess.run([model_fn_ops.train_op, model_fn_ops.loss]) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 462, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 786, in run run_metadata=run_metadata) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 744, in run return self._sess.run(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/training/monitored_session.py", line 899, in run run_metadata=run_metadata)) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 1157, in after_run induce_stop = m.step_end(self._last_step, result) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 356, in step_end return self.every_n_step_end(step, output) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/monitors.py", line 657, in every_n_step_end steps=self.eval_steps, metrics=self.metrics, name=self.name) File "/usr/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 280, in new_func return func(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 514, in evaluate log_progress=log_progress) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 810, in _evaluate_model eval_ops = self._get_eval_ops(features, labels, metrics) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1190, in _get_eval_ops features, labels, model_fn_lib.ModeKeys.EVAL) File "/usr/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1133, in _call_model_fn model_fn_results = self._model_fn(features, labels, **kwargs) File "/disk1/mouna/code/seq2seq/bin/train.py", line 164, in model_fn return model(features, labels, params) File "seq2seq/models/model_base.py", line 111, in call return self._build(features, labels, params) File "seq2seq/models/seq2seq_model.py", line 263, in _build decoder_output, _, = self.decode(encoder_output, features, labels) File "seq2seq/graph_utils.py", line 38, in func_wrapper return templated_func(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/template.py", line 276, in call return self._call_func(args, kwargs, check_for_new_variables=False) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/template.py", line 216, in _call_func result = self._func(*args, **kwargs) File "seq2seq/models/basic_seq2seq.py", line 124, in decode labels) File "seq2seq/models/basic_seq2seq.py", line 87, in _decode_train return decoder(decoder_initial_state, helper_train) File "seq2seq/graph_module.py", line 57, in call return self._template(*args, **kwargs) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/template.py", line 267, in call return self._call_func(args, kwargs, check_for_new_variables=False) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/template.py", line 216, in _call_func result = self._func(*args, **kwargs) File "seq2seq/decoders/rnn_decoder.py", line 110, in _build maximum_iterations=maximum_iterations) File "seq2seq/contrib/seq2seq/decoder.py", line 282, in dynamic_decode swap_memory=swap_memory) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2605, in while_loop result = context.BuildLoop(cond, body, loop_vars, shape_invariants) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2438, in BuildLoop pred, body, original_loop_vars, loop_vars, shape_invariants) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2388, in BuildLoop body_result = body(*packed_vars_for_body) File "seq2seq/contrib/seq2seq/decoder.py", line 242, in body decoder_finished) = decoder.step(time, inputs, state) File "seq2seq/decoders/attention_decoder.py", line 186, in step time=time, outputs=outputs, state=cell_state, sample_ids=sample_ids) File "seq2seq/contrib/seq2seq/helper.py", line 125, in next_inputs time=time, outputs=outputs, state=state, sample_ids=sample_ids) File "seq2seq/decoders/attention_decoder.py", line 154, in att_next_inputs name=name) File "seq2seq/contrib/seq2seq/helper.py", line 204, in next_inputs lambda: nest.map_structure(read_from_ta, self._input_tas)) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 1745, in cond _, res_f = context_f.BuildCondBranch(fn2) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 1639, in BuildCondBranch r = fn() File "seq2seq/contrib/seq2seq/helper.py", line 204, in lambda: nest.map_structure(read_from_ta, self._input_tas)) File "/usr/lib/python2.7/site-packages/tensorflow/python/util/nest.py", line 302, in map_structure structure[0], [func(*x) for x in entries]) File "seq2seq/contrib/seq2seq/helper.py", line 200, in read_from_ta return inp.read(next_time) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/tensor_array_ops.py", line 250, in read name=name) File "/usr/lib/python2.7/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2421, in _tensor_array_read_v3 name=name) File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op op_def=op_def) File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op original_op=self._default_original_op, op_def=op_def) File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1226, in init self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Tried to read from index 32 but array size is: 32 [[Node: model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3 = TensorArrayReadV3[_class=["loc:@model/att_seq2seq/decode/TrainingHelper/TensorArray"], dtype=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch, model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch_1/_463, model/att_seq2seq/decode/attention_decoder_1/decoder/while/CustomHelperNextInputs/TrainingHelperNextInputs/cond/TensorArrayReadV3/Switch_2)]]

Traceback (most recent call last): File "/usr/lib/python2.7/runpy.py", line 162, 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 "/usr/lib/python2.7/unittest/main.py", line 12, in main(module=None) File "/usr/lib/python2.7/unittest/main.py", line 94, in init self.parseArgs(argv) File "/usr/lib/python2.7/unittest/main.py", line 149, in parseArgs self.createTests() File "/usr/lib/python2.7/unittest/main.py", line 158, in createTests self.module) File "/usr/lib/python2.7/unittest/loader.py", line 130, in loadTestsFromNames suites = [self.loadTestsFromName(name, module) for name in names] File "/usr/lib/python2.7/unittest/loader.py", line 91, in loadTestsFromName module = import('.'.join(parts_copy)) File "seq2seq/init.py", line 24, in from seq2seq import contrib ImportError: cannot import name contrib When I run"python -m unittest seq2seq.test.pipeline_test",I got this error.Could someone tell me how to solve this problem?

When i try the WMT'16 EN-DE sample, encountered the following CUDA_ERROR_OUT_OF_MEMORY:

name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate (GHz) 1.531 pciBusID 0000:01:00.0 Total memory: 11.90GiB Free memory: 11.39GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: TITAN X (Pascal), pci bus id: 0000:01:00.0) E tensorflow/stream_executor/cuda/cuda_driver.cc:1002] failed to allocate 11.90G (12778405888 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY Traceback (most recent call last): File "/usr/lib/python3.4/runpy.py", line 170, in _run_module_as_main "main", mod_spec) File "/usr/lib/python3.4/runpy.py", line 85, in _run_code exec(code, run_globals) File "/media/sbai/7A9C9BED9C9BA1E5/DL/seq2seq/bin/train.py", line 251, in tf.app.run() File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/platform/app.py", line 44, in run _sys.exit(main(_sys.argv[:1] + flags_passthrough)) File "/media/sbai/7A9C9BED9C9BA1E5/DL/seq2seq/bin/train.py", line 246, in main schedule=FLAGS.schedule) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/learn_runner.py", line 106, in run return task() File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 459, in train_and_evaluate self.train(delay_secs=0) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/experiment.py", line 281, in train monitors=self._train_monitors + extra_hooks) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/util/deprecation.py", line 280, in new_func return func(*args, **kwargs) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 426, in fit loss = self._train_model(input_fn=input_fn, hooks=hooks) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 984, in _train_model _, loss = mon_sess.run([model_fn_ops.train_op, model_fn_ops.loss]) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/training/monitored_session.py", line 462, in run run_metadata=run_metadata) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/training/monitored_session.py", line 786, in run run_metadata=run_metadata) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/training/monitored_session.py", line 744, in run return self._sess.run(*args, **kwargs) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/training/monitored_session.py", line 883, in run feed_dict, options) File "/home/sbai/tf134/lib/python3.4/site-packages/tensorflow/python/training/monitored_session.py", line 909, in _call_hook_before_run request = hook.before_run(run_context) File "/media/sbai/7A9C9BED9C9BA1E5/DL/seq2seq/seq2seq/training/hooks.py", line 239, in before_run "predicted_tokens": self._pred_dict["predicted_tokens"], KeyError: 'predicted_tokens'

Env: TF1.0 GPU & Python3.4 & ubuntu14.04 I changed the batch size and the num_units into a smaller number, but still encountered the same error. I tried toy data, met the same error. Is it because I am using python3.4?

############################### update ############### I tried it on Python3.5, got the same error at the first try, and got following error when i tried again:

WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/contrib/learn/python/learn/monitors.py:267: BaseMonitor.init (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05. Instructions for updating: Monitors are deprecated. Please use tf.train.SessionRunHook. *** Error in `python3.5': double free or corruption (!prev): 0x0000000002870d90 *** Aborted (core dumped)

~/desktop/code/python_program/seq2seq$ python -m unittest seq2seq.test.pipeline_test .E

ERROR: test_train_infer (seq2seq.test.pipeline_test.PipelineTest) Tests training and inference scripts.

Traceback (most recent call last): File "seq2seq/test/pipeline_test.py", line 78, in test_train_infer os.path.join(BIN_FOLDER, "train.py")) UnicodeEncodeError: 'ascii' codec can't encode characters in position 11-12: ordinal not in range(128)

Ran 2 tests in 0.003s

FAILED (errors=1)

on centos Python 2.7, Tensorflow 1.01 when i run the command:python -m unittest seq2seq.test.pipeline_test there are some errors,like:

how can i fix it

In the original paper of SmartReply:

First, the elements of R (possible set of responses) are organized into a trie. Then, we conduct a left-to-right beam search, but only retain hypotheses that appear in the trie. This search process has complexity O(bl) for beam size b and maximum response length l. Both b and l are typically in the range of 10-30, so this method dramatically reduces the time to find the top responses and is a critical element of making this system deployable.

Would you please consider this feature and add a detailed task list to this issue for interested contributors.

I have install seq2seq sucessfully in window 10 with tensorflow-gpu (1.0) when I run the seq2seq.test.pipeline_test.py it Prompt errors:

Traceback (most recent call last): File "F:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\ops\script_ops.py", line 85, in call ret = func(*args) File "H:\java_pro\tensorflow\project_src\seq2seq-master\seq2seq-master\seq2seq\metrics\metric_specs.py", line 132, in _py_func return self.metric_fn(sliced_hypotheses, sliced_references) File "H:\java_pro\tensorflow\project_src\seq2seq-master\seq2seq-master\seq2seq\metrics\metric_specs.py", line 157, in metric_fn return bleu.moses_multi_bleu(hypotheses, references, lowercase=False) File "H:\java_pro\tensorflow\project_src\seq2seq-master\seq2seq-master\seq2seq\metrics\bleu.py", line 71, in moses_multi_bleu with open(hypothesis_file.name, "r") as read_pred: PermissionError: [Errno 13] Permission denied: 'C:\Users\gdy\AppData\Local\Temp\tmpjo9ekggj' W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:993] Internal: Failed to run py callback pyfunc_0: see error log. EF:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=3> outcome.errors.clear() F:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=4> outcome.errors.clear() F:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=5> outcome.errors.clear() F:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=6> outcome.errors.clear() F:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=7> outcome.errors.clear() F:\Program Files\Anaconda3\lib\unittest\case.py:628: ResourceWarning: unclosed file <_io.BufferedRandom name=8> outcome.errors.clear()

During training my model, I get a lot of warnings:

INFO:tensorflow:Starting evaluation at 2017-03-24-04:29:49
WARNING:tensorflow:multi-bleu.perl script returned non-zero exit code
WARNING:tensorflow:b'Illegal division by zero at /tmp/tmpu0_b8sc7 line 154, <STDIN> line 32.\n'
WARNING:tensorflow:multi-bleu.perl script returned non-zero exit code
WARNING:tensorflow:b'Illegal division by zero at /tmp/tmp7em8bjou line 154, <STDIN> line 64.\n'
WARNING:tensorflow:multi-bleu.perl script returned non-zero exit code
WARNING:tensorflow:b'Illegal division by zero at /tmp/tmp4osfwiwt line 154, <STDIN> line 96.\n'
...

Then I use something below to run the prediction, but get a blank file.

python -m bin.infer \
  --tasks "
    - class: DecodeText" \
  --model_dir $MODEL_DIR \
  --input_pipeline "
    class: ParallelTextInputPipeline
    params:
      source_files:
        - $DEV_SOURCES" \
  >  ${PRED_DIR}/predictions.txt

I'm trying to do text summarization, using the following command:

python -m bin.train \
  --config_paths="
      ./example_configs/nmt_medium.yml,
      ./example_configs/train_seq2seq.yml,
      ./example_configs/text_metrics_sp.yml" \
  --model_params "
      vocab_source: $VOCAB_SOURCE
      vocab_target: $VOCAB_TARGET" \
  --input_pipeline_train "
    class: ParallelTextInputPipeline
    params:
      source_files:
        - $TRAIN_SOURCES
      target_files:
        - $TRAIN_TARGETS" \
  --input_pipeline_dev "
    class: ParallelTextInputPipeline
    params:
       source_files:
        - $DEV_SOURCES
       target_files:
        - $DEV_TARGETS" \
  --batch_size 32 \
  --train_steps $TRAIN_STEPS \
  --output_dir $MODEL_DIR

I don't know where is wrong, and how to debug.

Hi all, Following the page at https://google.github.io/seq2seq/getting_started/, got error

user@localhost:~/Desktop/seq2seq$ pip install -e .
Obtaining file:///home/user/Desktop/seq2seq
Requirement already satisfied: numpy in /home/user/anaconda2/lib/python2.7/site-packages (from seq2seq==0.1)
Requirement already satisfied: matplotlib in /home/user/anaconda2/lib/python2.7/site-packages (from seq2seq==0.1)
Requirement already satisfied: pyyaml in /home/user/anaconda2/lib/python2.7/site-packages (from seq2seq==0.1)
Requirement already satisfied: pyrouge in /home/user/anaconda2/lib/python2.7/site-packages (from seq2seq==0.1)
Requirement already satisfied: six>=1.10 in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: python-dateutil in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: functools32 in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: subprocess32 in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: pytz in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: cycler>=0.10 in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=1.5.6 in /home/user/anaconda2/lib/python2.7/site-packages (from matplotlib->seq2seq==0.1)
Installing collected packages: seq2seq
  Running setup.py develop for seq2seq
Successfully installed seq2seq
user@localhost:~/Desktop/seq2seq$ python -m unittest seq2seq.test.pipeline_test
Traceback (most recent call last):
  File "/home/user/anaconda2/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/home/user/anaconda2/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/user/anaconda2/lib/python2.7/unittest/__main__.py", line 12, in 
    main(module=None)
  File "/home/user/anaconda2/lib/python2.7/unittest/main.py", line 94, in __init__
    self.parseArgs(argv)
  File "/home/user/anaconda2/lib/python2.7/unittest/main.py", line 149, in parseArgs
    self.createTests()
  File "/home/user/anaconda2/lib/python2.7/unittest/main.py", line 158, in createTests
    self.module)
  File "/home/user/anaconda2/lib/python2.7/unittest/loader.py", line 130, in loadTestsFromNames
    suites = [self.loadTestsFromName(name, module) for name in names]
  File "/home/user/anaconda2/lib/python2.7/unittest/loader.py", line 91, in loadTestsFromName
    module = __import__('.'.join(parts_copy))
  File "seq2seq/__init__.py", line 24, in 
    from seq2seq import contrib
ImportError: cannot import name contrib

PS: It should be pip install -e . at https://google.github.io/seq2seq/getting_started/

while running the pipeline unit test, i get this error

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 "/usr/lib/python2.7/unittest/__main__.py", line 12, in <module> main(module=None) File "/usr/lib/python2.7/unittest/main.py", line 94, in __init__ self.parseArgs(argv) File "/usr/lib/python2.7/unittest/main.py", line 149, in parseArgs self.createTests() File "/usr/lib/python2.7/unittest/main.py", line 158, in createTests self.module) File "/usr/lib/python2.7/unittest/loader.py", line 130, in loadTestsFromNames suites = [self.loadTestsFromName(name, module) for name in names] File "/usr/lib/python2.7/unittest/loader.py", line 91, in loadTestsFromName module = __import__('.'.join(parts_copy)) File "seq2seq/__init__.py", line 24, in <module> from seq2seq import contrib ImportError: cannot import name contrib

I have a naive question, if I have a pre-trained transformer model (pre-train task is a regression probelem), can I using the embedding of this model to training a decode model to decode embeddings to sequences, as like a translation task? I wonder if seq2seq can help me on this task. Thanks, anyway.

Got this error.

ERROR: seq2seq (unittest.loader._FailedTest)

ImportError: Failed to import test module: seq2seq Traceback (most recent call last): File "C:\Users\jtobo\AppData\Local\Programs\Python\Python39\lib\unittest\loader.py", line 154, in loadTestsFromName module = import(module_name) File "C:\Users\jtobo\seq2seq\seq2seq_init_.py", line 25, in from seq2seq import data File "C:\Users\jtobo\seq2seq\seq2seq\data_init_.py", line 17, in from seq2seq.data import input_pipeline File "C:\Users\jtobo\seq2seq\seq2seq\data\input_pipeline.py", line 32, in from tensorflow.contrib.slim.python.slim.data import tfexample_decoder ModuleNotFoundError: No module named 'tensorflow.contrib'

Ran 1 test in 0.000s

FAILED (errors=1)

seq2seq/test/pipeline_test.py:25: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp

Traceback (most recent call last):

File "seq2seq/test/pipeline_test.py", line 35, in <module>

`from seq2seq.test import utils as test_utils`

ModuleNotFoundError: No module named 'seq2seq'

I get this error when running the unit test pipeline_test. Any suggestions to solve the problem?

Not sure whats going on, but when I try the setup I get an error

ImportError: Failed to import test module: seq2seq
Traceback (most recent call last):
  File "C:\Users\charl\AppData\Local\Programs\Python\Python37\lib\unittest\loader.py", line 154, in loadTestsFromName
    module = __import__(module_name)
  File "C:\Users\charl\Documents\Chatbot\seq2seq\seq2seq\__init__.py", line 26, in <module>
    from seq2seq import decoders
  File "C:\Users\charl\Documents\Chatbot\seq2seq\seq2seq\decoders\__init__.py", line 20, in <module>
    from seq2seq.decoders.attention_decoder import *
  File "C:\Users\charl\Documents\Chatbot\seq2seq\seq2seq\decoders\attention_decoder.py", line 27, in <module>
    from seq2seq.contrib.seq2seq.helper import CustomHelper
  File "C:\Users\charl\Documents\Chatbot\seq2seq\seq2seq\contrib\seq2seq\helper.py", line 35, in <module>
    from tensorflow.contrib.distributions.python.ops import bernoulli
ImportError: cannot import name 'bernoulli' from 'tensorflow.contrib.distributions.python.ops' (C:\Users\charl\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\contrib\distributions\python\ops\__init__.py)


----------------------------------------------------------------------
Ran 1 test in 0.001s

FAILED (errors=1)

What is going on? How can I fix it?

I am trying to build a character based seq2seq model using tensorflow for food item names correction. The input/output would be like

IN: Cheessseee Quisadillas

OUT: Cheese Quesadillas

I have tried training a word level seq2seq but it does not give much good results. I have also read that we only used attention mechanism on long sequences and I have a Maximum of 6 word sentence(Item Name).

Apart from this, Can I use a language model like BERT or GPT for such task

Can anyone please suggest the changes or provide better resources for implementing the same.?