| /external/tensorflow/tensorflow/python/training/ |
| proximal_adagrad_test.py | 109 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| proximal_gradient_descent_test.py | 105 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| gradient_descent_test.py | 150 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| momentum_test.py | 250 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
277 return math_ops.reduce_sum(embedding_ops.embedding_lookup(var0, [[1]]))
|
| rmsprop_test.py | 174 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
198 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| ftrl_test.py | 116 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| factorization_ops.py | [all...] |
| clustering_ops.py | 33 from tensorflow.python.ops.embedding_ops import embedding_lookup
606 return embedding_lookup(self._inputs, indices, partition_strategy='div')
[all...] |
| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| adagrad_test.py | 219 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) # pylint: disable=cell-var-from-loop
351 embedding_ops.embedding_lookup(var_repeated, [0, 0])) # pylint: disable=cell-var-from-loop
355 embedding_ops.embedding_lookup(var_aggregated, [0])) # pylint: disable=cell-var-from-loop
|
| gradient_descent_test.py | 160 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) # pylint: disable=cell-var-from-loop
449 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
477 return math_ops.reduce_sum(embedding_ops.embedding_lookup(var0, [[1]]))
[all...] |
| rmsprop_test.py | 329 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) # pylint: disable=cell-var-from-loop
357 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) # pylint: disable=cell-var-from-loop
|
| ftrl_test.py | 118 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x) # pylint: disable=cell-var-from-loop
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/ |
| rnn_ptb.py | 95 return tf.nn.embedding_lookup(self.embedding, x)
|
| /external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
| core_rnn_cell.py | 265 embedded = embedding_ops.embedding_lookup(embedding,
|
| /external/tensorflow/tensorflow/python/ops/ |
| control_flow_ops_test.py | 203 embedding = embedding_ops.embedding_lookup(embedding_matrix + 0.0, [0])
225 embedding = embedding_ops.embedding_lookup(embedding_matrix, [0])
246 embedding = embedding_ops.embedding_lookup(embedding_matrix, [0])
260 embedding = embedding_ops.embedding_lookup(embedding_matrix, [0])
[all...] |
| clustering_ops.py | 34 from tensorflow.python.ops.embedding_ops import embedding_lookup
607 return embedding_lookup(self._inputs, indices, partition_strategy='div')
[all...] |
| nn_impl.py | [all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| embedding_ops.py | 122 with ops.name_scope(name, "embedding_lookup",
373 result = embedding_ops.embedding_lookup(
463 """Version of embedding_lookup that avoids duplicate lookups.
466 Same interface as embedding_lookup. Except it supports multi-dimensional `ids`
492 unique_embeddings = embedding_ops.embedding_lookup(params, unique_ids,
611 is `"mod"`. See `tf.nn.embedding_lookup` for more details.
[all...] |
| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| momentum_test.py | 248 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
275 return math_ops.reduce_sum(embedding_ops.embedding_lookup(var0, [[1]]))
|
| rmsprop_test.py | 173 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
195 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
|
| /external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
| helper.py | 330 or the `params` argument for `embedding_lookup`.
349 lambda ids: embedding_ops.embedding_lookup(embedding, ids))
566 or the `params` argument for `embedding_lookup`. The returned tensor
579 lambda ids: embedding_ops.embedding_lookup(embedding, ids))
644 or the `params` argument for `embedding_lookup`. The returned tensor
|
| sampler.py | 300 or the `params` argument for `embedding_lookup`.
331 lambda ids: embedding_ops.embedding_lookup(embedding, ids))
505 (argmax ids), or the `params` argument for `embedding_lookup`. The
507 `embedding_ops.embedding_lookup`.
549 lambda ids: embedding_ops.embedding_lookup(embedding, ids))
600 (argmax ids), or the `params` argument for `embedding_lookup`. The
|
| beam_search_decoder.py | 647 or the `params` argument for `embedding_lookup`.
683 lambda ids: embedding_ops.embedding_lookup(embedding, ids))
[all...] |
| /external/tensorflow/tensorflow/contrib/feature_column/python/feature_column/ |
| sequence_feature_column_test.py | [all...] |
| /external/tensorflow/tensorflow/python/feature_column/ |
| sequence_feature_column_test.py | [all...] |
