/external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/python/ops/ |
D | training_ops.py | 73 dl_du = array_ops.expand_dims(grad, 2) 81 du_df = array_ops.expand_dims( 95 df_dx = -array_ops.expand_dims(tree_weights_tensor, 0) 102 df_dt = -array_ops.expand_dims(input_data_tensor, 1) 108 df_db = array_ops.expand_dims( 109 array_ops.expand_dims(array_ops.ones_like(tree_thresholds_tensor), 0), 2) 159 dl_du = array_ops.expand_dims(unpack_path_op(path_tensor, routing_grad), 2) 167 du_df = array_ops.expand_dims(du_df_raw, 2) 175 df_dx = array_ops.expand_dims(df_dx_raw, 0) 188 df_db = array_ops.expand_dims(array_ops.expand_dims(df_db_raw, 0), 2) [all …]
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/external/tensorflow/tensorflow/contrib/crf/python/kernel_tests/ |
D | crf_test.py | 57 inputs=array_ops.expand_dims(inputs, 0), 58 tag_indices=array_ops.expand_dims(tag_indices, 0), 59 sequence_lengths=array_ops.expand_dims(sequence_lengths, 0), 79 tag_indices=array_ops.expand_dims(tag_indices, 0), 80 sequence_lengths=array_ops.expand_dims(sequence_lengths, 0), 81 inputs=array_ops.expand_dims(inputs, 0)) 95 tag_indices=array_ops.expand_dims(tag_indices, 0), 96 sequence_lengths=array_ops.expand_dims(sequence_lengths, 0), 139 inputs=array_ops.expand_dims(inputs, 0), 140 tag_indices=array_ops.expand_dims(tag_indices, 0), [all …]
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_ExpandDims.pbtxt | 28 channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`, 35 shape(expand_dims(t, 0)) ==> [1, 2] 36 shape(expand_dims(t, 1)) ==> [2, 1] 37 shape(expand_dims(t, -1)) ==> [2, 1] 40 shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5] 41 shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5] 42 shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]
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/external/tensorflow/tensorflow/contrib/crf/python/ops/ |
D | crf.py | 206 offsets = array_ops.expand_dims( 208 offsets += array_ops.expand_dims(math_ops.range(max_seq_len) * num_tags, 0) 276 self._transition_params = array_ops.expand_dims(transition_params, 0) 300 state = array_ops.expand_dims(state, 2) 336 v = np.expand_dims(trellis[t - 1], 1) + transition_params 362 self._transition_params = array_ops.expand_dims(transition_params, 0) 388 state = array_ops.expand_dims(state, 2) # [B, O, 1] 437 new_tags = array_ops.expand_dims( 465 decode_tags = array_ops.expand_dims( 496 initial_state = array_ops.expand_dims(initial_state, axis=-1) # [B, 1]
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/external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
D | factorization_ops_test_utils.py | 86 ind = (np.concatenate((np.expand_dims(indices[1], 1), 87 np.expand_dims(indices[0], 1)), 1).astype(np.int64) if 88 transpose else np.concatenate((np.expand_dims(indices[0], 1), 89 np.expand_dims(indices[1], 1)), 118 wr = (array_ops.expand_dims(row_weights, 1) if row_weights is not None 120 wc = (array_ops.expand_dims(col_weights, 0) if col_weights is not None
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D | gmm_ops.py | 182 means = array_ops.expand_dims(initial_means, 1) 185 means = array_ops.expand_dims( 193 array_ops.expand_dims(cov, 0), [self._num_classes, 1, 1]) 198 array_ops.expand_dims(array_ops.diag_part(cov), 0), 273 shard = array_ops.expand_dims(shard, 0) 319 cov_expanded = array_ops.expand_dims(1.0 / (self._covs + 1e-3), 2) 358 probs = array_ops.expand_dims(self._probs[shard_id], 0) 380 w_mul_x = array_ops.expand_dims( 389 array_ops.expand_dims(x_trans[k, :, :] * self._w[shard_id][:, k], 0) 431 new_covs.append(array_ops.expand_dims(new_cov, 0)) [all …]
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D | factorization_ops.py | 852 col_ids = array_ops.expand_dims(math_ops.cast(all_col_ids, dtypes.int64), 1) 853 row_ids = array_ops.expand_dims(math_ops.cast(all_row_ids, dtypes.int64), 1) 924 total_lhs = array_ops.expand_dims(total_lhs, 0) + partial_lhs 925 total_rhs = array_ops.expand_dims(total_rhs, -1) 954 if self._row_weights is None else array_ops.expand_dims( 957 if self._col_weights is None else array_ops.expand_dims(
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/external/tensorflow/tensorflow/tools/compatibility/testdata/ |
D | test_file_v0_11.py | 97 tf.expand_dims([[1, 2], [3, 4]], dim=1).eval(), 121 self.assertAllEqual(tf.expand_dims(tf.squeeze(a, [0]), 0).eval(), 123 self.assertAllEqual(tf.squeeze(tf.expand_dims(a, 1), [1]).eval(), 126 tf.expand_dims( 132 tf.expand_dims( 138 tf.expand_dims( 169 batched_mat = tf.expand_dims(mat, [0]) 172 self.assertAllEqual(result_batched, np.expand_dims(result, 0))
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | conv1d_test.py | 38 x = array_ops.expand_dims(x, 0) # Add batch dimension 39 x = array_ops.expand_dims(x, 2) # And depth dimension 41 filters = array_ops.expand_dims(filters, 1) # in_channels 42 filters = array_ops.expand_dims(filters, 2) # out_channels
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D | attention_ops_test.py | 59 array_ops.expand_dims(array_ops.expand_dims(t_rows, 0), 3), 73 array_ops.expand_dims(array_ops.expand_dims(t_cols, 0), 3),
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D | shape_ops_test.py | 176 np_ans = np.expand_dims(x, axis=dim) 178 tensor = array_ops.expand_dims(x, dim) 232 self.assertRaises(ValueError, array_ops.expand_dims, 234 self.assertRaises(ValueError, array_ops.expand_dims, 236 self.assertRaises(ValueError, array_ops.expand_dims, 238 self.assertRaises(ValueError, array_ops.expand_dims, 245 squeezed = array_ops.expand_dims(inp, 1) 254 self.assertAllEqual([7], array_ops.expand_dims(inp, 0).eval()) 255 self.assertAllEqual([7], array_ops.expand_dims(inp, -1).eval()) 258 self.assertAllEqual([True], array_ops.expand_dims(inp, 0).eval()) [all …]
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D | draw_bounding_box_op_test.py | 84 bboxes = array_ops.expand_dims(bboxes, 0) 87 image = array_ops.expand_dims(image, 0)
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/external/tensorflow/tensorflow/contrib/solvers/python/ops/ |
D | lanczos.py | 97 return array_ops.expand_dims(tarray.read(i), -1) 226 alpha = array_ops.expand_dims(alpha, 0) 228 beta = array_ops.expand_dims(beta, 0) 231 beta = array_ops.expand_dims(beta[:-1], 0) 233 zero_column = array_ops.expand_dims(
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D | linear_equations.py | 108 rhs = array_ops.expand_dims(rhs, -1) 110 x = array_ops.expand_dims( 114 x = array_ops.expand_dims(x, -1)
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D | least_squares.py | 97 rhs = array_ops.expand_dims(rhs, -1) 101 x = array_ops.expand_dims(
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/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
D | beam_search_decoder.py | 86 tiled = array_ops.tile(array_ops.expand_dims(t, 1), tiling) 228 array_ops.expand_dims(self._start_tokens, 1), [1, self._beam_width]) 550 total_probs = array_ops.expand_dims(beam_state.log_probs, 2) + step_log_probs 561 lengths_to_add *= array_ops.expand_dims(add_mask, 2) 563 lengths_to_add + array_ops.expand_dims(prediction_lengths, 2)) 733 array_ops.expand_dims(finished, 2), [1, 1, vocab_size]) 804 range_ = array_ops.expand_dims(math_ops.range(batch_size) * range_size, 1)
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/external/tensorflow/tensorflow/contrib/training/python/training/ |
D | sequence_queueing_state_saver.py | 1079 sequence_count_vec = array_ops.expand_dims(sequence_count, 0) 1099 array_ops.slice(current_keys, [1], [-1]), array_ops.expand_dims( 1114 array_ops.expand_dims(sequence_count, 0), 1115 array_ops.expand_dims(self._num_unroll, 0), 1131 array_ops.expand_dims(v, 0), 1134 array_ops.expand_dims(sequence_count, 0), 1673 values = array_ops.tile(sp_tensor.values, array_ops.expand_dims(n, 0)) 1675 [array_ops.expand_dims(value_length, 0), sp_tensor.dense_shape], 0) 1680 array_ops.expand_dims(sp_tensor.indices, 0), 1695 ind = array_ops.expand_dims(ind, 1) [all …]
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/external/tensorflow/tensorflow/python/ops/ |
D | image_ops_impl.py | 586 image = array_ops.expand_dims(image, 0) 589 image = array_ops.expand_dims(image, 0) 669 image = array_ops.expand_dims(image, 0) 672 image = array_ops.expand_dims(image, 0) 746 image = array_ops.expand_dims(image, 0) 749 image = array_ops.expand_dims(image, 0) 893 images = array_ops.expand_dims(images, 0) 1275 gray_float = array_ops.expand_dims(gray_float, -1) 1295 rank_1 = array_ops.expand_dims(array_ops.rank(images) - 1, 0) 1297 [array_ops.expand_dims(3, 0)])
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D | linalg_grad.py | 245 array_ops.expand_dims(e, -2) - array_ops.expand_dims(e, -1)), 341 array_ops.expand_dims(s2, -2) - array_ops.expand_dims(s2, -1)),
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/external/tensorflow/tensorflow/contrib/kfac/python/ops/ |
D | loss_functions.py | 438 ones_slice = array_ops.expand_dims( 536 mean_slice = array_ops.expand_dims(mean_slice, axis=-1) 544 var_slice = array_ops.expand_dims(var_slice, axis=-1) 682 sqrt_probs_slice = array_ops.expand_dims(sqrt_probs[:, index[0]], -1) 743 probs_slice = array_ops.expand_dims(self._probs[:, index[0]], -1)
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/external/tensorflow/tensorflow/examples/wav_to_spectrogram/ |
D | wav_to_spectrogram.cc | 70 Output expand_dims = in WavToSpectrogram() local 72 Output squeeze = Squeeze(root.WithOpName("squeeze"), expand_dims, in WavToSpectrogram()
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/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
D | merge.py | 130 x = K.expand_dims(x, 1) 142 new_shape = K.concatenate([x_shape[1:], K.expand_dims(batch_size)]) 166 [K.expand_dims(batch_size), y_shape[:y_ndim - 1]]) 210 masks = [K.expand_dims(m, 0) for m in mask if m is not None] 424 masks.append(K.expand_dims(mask_i))
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/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
D | ar_model_test.py | 151 predict_times = np.expand_dims(np.concatenate( 153 predict_true_values = np.expand_dims(np.concatenate( 155 state_times = np.expand_dims(train_data_times[:input_window_size], 0) 156 state_values = np.expand_dims(
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
D | dynamic_rnn_estimator_test.py | 319 array_ops.expand_dims(math_ops.range(cell_size), 0) 374 inputs = array_ops.expand_dims( 432 inputs = array_ops.expand_dims( 529 inputs = array_ops.expand_dims( 589 inputs = array_ops.expand_dims( 670 inputs = array_ops.expand_dims(sequences, 2) 722 inputs = array_ops.expand_dims(math_ops.to_float(random_sequence), 2)
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/external/tensorflow/tensorflow/contrib/signal/python/kernel_tests/ |
D | shape_ops_test.py | 38 tensor = array_ops.expand_dims(tensor, 0) 45 expected = np.expand_dims(expected, axis=0) 53 tensor = array_ops.expand_dims(tensor, 0) 62 expected = np.expand_dims(expected, axis=0)
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