/external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
D | blocks_test.py | 136 dy1, dy2 = tf.split(dy, num_or_size_splits=2, axis=1) 146 x1, x2 = tf.split(x, num_or_size_splits=2, axis=1) 165 dy1, dy2 = tf.split(dy, num_or_size_splits=2, axis=1) 175 x1, x2 = tf.split(x, num_or_size_splits=2, axis=1) 199 dy1, dy2 = tf.split(dy, num_or_size_splits=2, axis=1) 209 x1, x2 = tf.split(x, num_or_size_splits=2, axis=1) 239 dy1, dy2 = tf.split(dy, num_or_size_splits=2, axis=1) 249 x1_true, x2_true = tf.split(x_true, num_or_size_splits=2, axis=1)
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D | blocks.py | 452 return tf.split(net, num_or_size_splits=2, axis=self.axis)
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | split_op_test.py | 70 num_or_size_splits=constant_op.constant(2), 227 tf_ans = array_ops.split(value=x, num_or_size_splits=num, axis=dim) 250 tf_ans = array_ops.split(value=x, num_or_size_splits=num, axis=dim) 298 value=inp, num_or_size_splits=num_split, axis=split_dim)) 320 s = array_ops.split(value=inp_tensor, num_or_size_splits=4, axis=1) 338 array_ops.split(value=[[0, 1], [2, 3]], num_or_size_splits=4, axis=2) 342 array_ops.split(value=[[0, 1], [2, 3]], num_or_size_splits=4, axis=-3) 346 array_ops.split(value=[0, 1, 2, 3], num_or_size_splits=3, axis=0) 351 num_or_size_splits=4, 359 num_or_size_splits=4,
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/external/tensorflow/tensorflow/python/tpu/ |
D | tpu_feed.py | 71 num_or_size_splits = [ceil_ratio] * num_full_slots + [left_over] 72 if len(num_or_size_splits) < dim: 73 num_or_size_splits += [0] * (dim - len(num_or_size_splits)) 78 x, num_or_size_splits=num_or_size_splits, axis=axis))
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/external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
D | classifier_metrics_impl.py | 346 images, num_or_size_splits=num_batches) 499 real_images, num_or_size_splits=num_batches) 501 generated_images, num_or_size_splits=num_batches) 889 real_images, num_or_size_splits=num_classifier_batches) 891 generated_images, num_or_size_splits=num_classifier_batches)
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/external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
D | rnn_cells.py | 145 c, h = array_ops.split(value=state, num_or_size_splits=2, axis=one) 153 value=gate_inputs, num_or_size_splits=4, axis=one) 317 value=lstm_matrix, num_or_size_splits=4, axis=1)
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/external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
D | rnn_cell.py | 278 j, f, o = array_ops.split(value=lstm_matrix, num_or_size_splits=3, axis=1) 446 value=lstm_matrix, num_or_size_splits=4, axis=1) 768 value=lstm_matrix_freq, num_or_size_splits=num_gates, axis=1) 772 value=lstm_matrix_freq, num_or_size_splits=num_gates, axis=1) 784 value=lstm_matrix_time, num_or_size_splits=num_gates, axis=1) 788 value=lstm_matrix_time, num_or_size_splits=num_gates, axis=1) 1445 i, j, f, o = array_ops.split(value=concat, num_or_size_splits=4, axis=1) 1582 axis=1, num_or_size_splits=self._NAS_BASE, value=m_matrix) 1584 axis=1, num_or_size_splits=self._NAS_BASE, value=inputs_matrix) 1706 axis=1, num_or_size_splits=2, value=rnn_matrix) [all …]
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/external/tensorflow/tensorflow/contrib/linear_optimizer/python/ |
D | sdca_optimizer.py | 134 value=sparse_indices, num_or_size_splits=2, axis=1)[0], [-1]), 137 value=sparse_indices, num_or_size_splits=2, axis=1)[1], [-1]),
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/external/tensorflow/tensorflow/python/eager/ |
D | pywrap_tfe_test.py | 214 array_ops.split(value=[1, 2, 3], num_or_size_splits=-1) 219 array_ops.split(value=[1, 2, 3], num_or_size_splits=0)
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/external/tensorflow/tensorflow/compiler/tests/ |
D | lstm.py | 70 value=xmw, num_or_size_splits=4, axis=1)
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D | binary_ops_test.py | 1222 lambda x, y: array_ops.split(value=y, num_or_size_splits=3, axis=x), 1235 lambda x, y: array_ops.split(value=y, num_or_size_splits=2, axis=x), 1246 return array_ops.split(value=y, num_or_size_splits=[2, 3], axis=x)
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/external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
D | factorization_ops_test_utils.py | 127 num_or_size_splits=2)
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D | wals_test.py | 75 value=sp_x.indices, num_or_size_splits=2, axis=1)
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D | factorization_ops.py | 874 value=sp_input.indices, num_or_size_splits=2, axis=1)
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/external/tensorflow/tensorflow/python/ops/ |
D | array_ops.py | 1472 def split(value, num_or_size_splits, axis=0, num=None, name="split"): argument 1520 size_splits = ops.convert_to_tensor(num_or_size_splits) 1521 if isinstance(num_or_size_splits, 1524 axis=axis, num_split=num_or_size_splits, value=value, name=name) 1529 "to split. Argument provided: %s" % (num_or_size_splits,)) 1536 raise ValueError("Cannot infer num from shape %s" % num_or_size_splits)
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D | rnn_cell_impl.py | 585 r, u = array_ops.split(value=value, num_or_size_splits=2, axis=1) 764 c, h = array_ops.split(value=state, num_or_size_splits=2, axis=one) 772 value=gate_inputs, num_or_size_splits=4, axis=one) 1023 value=lstm_matrix, num_or_size_splits=4, axis=1)
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/batch/ |
D | categorical_split_handler.py | 130 self._sparse_int_column.indices, num_or_size_splits=2, axis=1)
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D | ordinal_split_handler.py | 670 sparse_column_indices, num_or_size_splits=2, axis=1)
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/external/tensorflow/tensorflow/contrib/quantize/python/ |
D | graph_matcher_test.py | 92 y0, y1 = array_ops.split(y, num_or_size_splits=2, axis=0)
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/external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/ |
D | sdca_ops_test.py | 92 num_or_size_splits=2, 100 num_or_size_splits=2,
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/external/tensorflow/tensorflow/contrib/grid_rnn/python/ops/ |
D | grid_rnn_cell.py | 295 value=inputs, num_or_size_splits=len(conf.inputs), axis=1)
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/external/tensorflow/tensorflow/lite/python/ |
D | convert_test.py | 62 value=in_tensor, num_or_size_splits=[1, 1, 1, 1], axis=0)
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/external/tensorflow/tensorflow/contrib/tensor_forest/python/ |
D | tensor_forest.py | 396 value=input_data, num_or_size_splits=self.params.num_features, axis=1)
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/external/tensorflow/tensorflow/contrib/linear_optimizer/python/ops/ |
D | sdca_ops.py | 561 u, num_or_size_splits=[v.shape.as_list()[0] for v in w])
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | recurrent.py | 2234 self.kernel, num_or_size_splits=4, axis=1) 2241 self.bias, num_or_size_splits=4, axis=0) 2270 z = array_ops.split(z, num_or_size_splits=4, axis=1)
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