diff options
| author |  Jianwei Xie <xiejw@google.com> | 2016-12-07 14:03:04 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2016-12-07 14:23:09 -0800 |
| commit | 4139949dc8c1919efc666fd6369a741af4f13990 (patch) | |
| tree | 0ce8f58b524fbadef030b00371d84cccc8a394d9 | |
| parent | 8b86c22185e20b8d69f86df0b964d2adcca0a1d4 (diff) | |
Use tf.contrib.legacy_seq2seq instead of tf.nn.seq2seq.
Change: 141353751
| -rw-r--r-- | tensorflow/models/rnn/ptb/ptb_word_lm.py | 2 | ||||
| -rw-r--r-- | tensorflow/models/rnn/seq2seq.py | 3 | ||||
| -rw-r--r-- | tensorflow/models/rnn/translate/seq2seq_model.py | 6 |
3 files changed, 6 insertions, 5 deletions
diff --git a/tensorflow/models/rnn/ptb/ptb_word_lm.py b/tensorflow/models/rnn/ptb/ptb_word_lm.py index f4560a7a28..df1939e0f3 100644 --- a/tensorflow/models/rnn/ptb/ptb_word_lm.py +++ b/tensorflow/models/rnn/ptb/ptb_word_lm.py @@ -146,7 +146,7 @@ class PTBModel(object): "softmax_w", [size, vocab_size], dtype=data_type()) softmax_b = tf.get_variable("softmax_b", [vocab_size], dtype=data_type()) logits = tf.matmul(output, softmax_w) + softmax_b - loss = tf.nn.seq2seq.sequence_loss_by_example( + loss = tf.contrib.legacy_seq2seq.sequence_loss_by_example( [logits], [tf.reshape(input_.targets, [-1])], [tf.ones([batch_size * num_steps], dtype=data_type())]) diff --git a/tensorflow/models/rnn/seq2seq.py b/tensorflow/models/rnn/seq2seq.py index 0c3e645f44..ff487f9475 100644 --- a/tensorflow/models/rnn/seq2seq.py +++ b/tensorflow/models/rnn/seq2seq.py @@ -18,4 +18,5 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -raise ImportError("This module is deprecated. Use tf.nn.seq2seq instead.") +raise ImportError( + "This module is deprecated. Use tf.contrib.legacy_seq2seq instead.") diff --git a/tensorflow/models/rnn/translate/seq2seq_model.py b/tensorflow/models/rnn/translate/seq2seq_model.py index 2d73372f6d..b25e61bd23 100644 --- a/tensorflow/models/rnn/translate/seq2seq_model.py +++ b/tensorflow/models/rnn/translate/seq2seq_model.py @@ -123,7 +123,7 @@ class Seq2SeqModel(object): # The seq2seq function: we use embedding for the input and attention. def seq2seq_f(encoder_inputs, decoder_inputs, do_decode): - return tf.nn.seq2seq.embedding_attention_seq2seq( + return tf.contrib.legacy_seq2seq.embedding_attention_seq2seq( encoder_inputs, decoder_inputs, cell, @@ -153,7 +153,7 @@ class Seq2SeqModel(object): # Training outputs and losses. if forward_only: - self.outputs, self.losses = tf.nn.seq2seq.model_with_buckets( + self.outputs, self.losses = tf.contrib.legacy_seq2seq.model_with_buckets( self.encoder_inputs, self.decoder_inputs, targets, self.target_weights, buckets, lambda x, y: seq2seq_f(x, y, True), softmax_loss_function=softmax_loss_function) @@ -165,7 +165,7 @@ class Seq2SeqModel(object): for output in self.outputs[b] ] else: - self.outputs, self.losses = tf.nn.seq2seq.model_with_buckets( + self.outputs, self.losses = tf.contrib.legacy_seq2seq.model_with_buckets( self.encoder_inputs, self.decoder_inputs, targets, self.target_weights, buckets, lambda x, y: seq2seq_f(x, y, False), |