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Hi,
when I review this code, I found the depth of encoder and decoder must be the same.
as " self.depth = config['depth']" which is used in contructing encoder and decoder.
And I try to set different depths, just get the following error:
Traceback (most recent call last):
File "train.py", line 301, in
tf.app.run()
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "train.py", line 297, in main
train()
File "train.py", line 145, in train
model = create_model(sess, FLAGS)
File "train.py", line 82, in create_model
model = Seq2SeqModel(config, 'train')
File "/home/aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 72, in init
self.build_model()
File "/home//aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 81, in build_model
self.build_decoder()
File "/home/aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 287, in build_decoder
maximum_iterations=max_decoder_length))
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/decoder.py", line 286, in dynamic_decode
swap_memory=swap_memory)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2816, in while_loop
result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2640, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2590, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/decoder.py", line 234, in body
decoder_finished) = decoder.step(time, inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/basic_decoder.py", line 138, in step
cell_outputs, cell_state = self._cell(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 183, in call
return super(RNNCell, self).call(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 575, in call
outputs = self.call(inputs, *args, **kwargs)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 1066, in call
cur_inp, new_state = cell(cur_inp, cur_state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 951, in call
outputs, new_state = self._cell(inputs, state, scope=scope)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 891, in call
output, new_state = self._cell(inputs, state, scope)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 183, in call
return super(RNNCell, self).call(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 575, in call
outputs = self.call(inputs, *args, **kwargs)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 591, in call
(c_prev, m_prev) = state
ValueError: too many values to unpack
Any way, do you have any suggetion to solve this problem ?
The text was updated successfully, but these errors were encountered:
Hi,
when I review this code, I found the depth of encoder and decoder must be the same.
as " self.depth = config['depth']" which is used in contructing encoder and decoder.
And I try to set different depths, just get the following error:
Traceback (most recent call last):
File "train.py", line 301, in
tf.app.run()
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "train.py", line 297, in main
train()
File "train.py", line 145, in train
model = create_model(sess, FLAGS)
File "train.py", line 82, in create_model
model = Seq2SeqModel(config, 'train')
File "/home/aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 72, in init
self.build_model()
File "/home//aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 81, in build_model
self.build_decoder()
File "/home/aldy/work/nmt/tf-seq/tf-seq2seq-master/seq2seq_model.py", line 287, in build_decoder
maximum_iterations=max_decoder_length))
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/decoder.py", line 286, in dynamic_decode
swap_memory=swap_memory)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2816, in while_loop
result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2640, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 2590, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "/home//aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/decoder.py", line 234, in body
decoder_finished) = decoder.step(time, inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/contrib/seq2seq/python/ops/basic_decoder.py", line 138, in step
cell_outputs, cell_state = self._cell(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 183, in call
return super(RNNCell, self).call(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 575, in call
outputs = self.call(inputs, *args, **kwargs)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 1066, in call
cur_inp, new_state = cell(cur_inp, cur_state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 951, in call
outputs, new_state = self._cell(inputs, state, scope=scope)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 891, in call
output, new_state = self._cell(inputs, state, scope)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 183, in call
return super(RNNCell, self).call(inputs, state)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/layers/base.py", line 575, in call
outputs = self.call(inputs, *args, **kwargs)
File "/home/aldy/.local/lib/python2.7/site-packages/tensorflow/python/ops/rnn_cell_impl.py", line 591, in call
(c_prev, m_prev) = state
ValueError: too many values to unpack
Any way, do you have any suggetion to solve this problem ?
The text was updated successfully, but these errors were encountered: