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author | Jonathan Hseu <jhseu@google.com> | 2017-08-25 14:01:05 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2017-08-25 14:04:48 -0700 |
commit | 008910f1122d115a6d7430bfcc63cf4296c7467d (patch) | |
tree | e50199dcceed004cecc8510f9251f5e04734800f /tensorflow/examples/tutorials | |
parent | 005a88f6cc6e4e8c94a4f2d1980737855c4592f4 (diff) |
Merge changes from github.
END_PUBLIC
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Commit b30ce4714 authored by James Qin<jamesqin@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Revamp CudnnRNN Saveables
1. Use a lossy way to save/restore cudnn biases during checkpointing.
Cudnn uses 2 biases each gate for all RNNs while tf uses one. To allow cudnn checkpoints
to be compatible with both Cudnn and platform-independent impls, previously both
individual bias and summed biases each gate were stored.
The new way only stores the bias sum for each gate, and split it half-half when
restoring from a cudnn graph. Doing this does not cause problems since RNNs do not use
weight-decay to regularize.
2. Use inheritance instead of branching
* Split RNNParamsSaveable to 1 base class and 4 subclasses.
* Extract common routines and only overwrite rnn-type-specific pieces in subclasses.
PiperOrigin-RevId: 166413989
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Commit ebc421daf authored by Alan Yee<alyee@ucsd.edu>
Committed by Jonathan Hseu<vomjom@vomjom.net>:
Update documentation for contrib (#12424)
* Update __init__.py
Remove ## for standardization of api docs
* Create README.md
Add README to define this directory's purpose
* Update __init.py
Markdown styling does not show up well in api docs
* Update README.md
Add short mention of describing what to deprecate
* Update README.md
Capitalize title
* Update README.md
Revert README change
* Delete README.md
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Commit fd295394d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Use latest version of nsync library, which now allows use of cmake on MacOS.
PiperOrigin-RevId: 166411437
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Commit 587d728e0 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Refactor reduce-precision-insertion filters, add several more options.
In particular, this adds the ability to add reduce-precision operations after fusion nodes based on the contents of those fusion nodes, and the ability to filter operations based on the "op_name" metadata.
PiperOrigin-RevId: 166408392
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Commit 3142f8ef5 authored by Ali Yahya<alive@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Steps toward making ResourceVariables compatible with Eager.
This change forces the value of the reuse flag in variable scopes to be tf.AUTO_REUSE when in Eager mode.
This change also adds comprehensive Eager tests for ResourceVariable.
PiperOrigin-RevId: 166408161
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Commit b2ce45150 authored by Igor Ganichev<iga@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make Graph::IsValidNode public
It can be reimplemented with existing public APIs, but instead of doing so,
making this one public seems better.
PiperOrigin-RevId: 166407897
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Commit 0a2f40e92 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA::CPU] Fix HLO profiling in parallel CPU backend.
PiperOrigin-RevId: 166400211
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Commit c4a58e3fd authored by Yao Zhang<yaozhang@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Identify frame ids for all nodes in a graph.
PiperOrigin-RevId: 166397615
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Commit 989713f26 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
BEGIN_PUBLIC
Automated g4 rollback of changelist 166294015
PiperOrigin-RevId: 166521502
Diffstat (limited to 'tensorflow/examples/tutorials')
-rw-r--r-- | tensorflow/examples/tutorials/word2vec/word2vec_basic.py | 17 |
1 files changed, 7 insertions, 10 deletions
diff --git a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py index 6c93617ae5..d73b1c6373 100644 --- a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py +++ b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py @@ -78,10 +78,8 @@ def build_dataset(words, n_words): data = list() unk_count = 0 for word in words: - if word in dictionary: - index = dictionary[word] - else: - index = 0 # dictionary['UNK'] + index = dictionary.get(word, 0) + if index == 0: # dictionary['UNK'] unk_count += 1 data.append(index) count[0][1] = unk_count @@ -110,14 +108,13 @@ def generate_batch(batch_size, num_skips, skip_window): buffer.extend(data[data_index:data_index + span]) data_index += span for i in range(batch_size // num_skips): - target = skip_window # target label at the center of the buffer - targets_to_avoid = [skip_window] + context_words = [w for w in range(span) if w != skip_window] + random.shuffle(context_words) + words_to_use = collections.deque(context_words) for j in range(num_skips): - while target in targets_to_avoid: - target = random.randint(0, span - 1) - targets_to_avoid.append(target) batch[i * num_skips + j] = buffer[skip_window] - labels[i * num_skips + j, 0] = buffer[target] + context_word = words_to_use.pop() + labels[i * num_skips + j, 0] = buffer[context_word] if data_index == len(data): buffer[:] = data[:span] data_index = span |