/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/tools/compatibility/testdata/ |
D | test_file_v0_11.py | 99 tf.expand_dims([[1, 2], [3, 4]], axis=1).eval(), 125 self.assertAllEqual(tf.expand_dims(tf.squeeze(a, [0]), 0).eval(), 127 self.assertAllEqual(tf.squeeze(tf.expand_dims(a, 1), [1]).eval(), 130 tf.expand_dims(tf.squeeze([[1, 2, 3]], axis=[0]), dim=0).eval(), a) 132 tf.squeeze(tf.expand_dims([[1, 2, 3]], dim=1), axis=[1]).eval(), a) 135 tf.squeeze(tf.expand_dims([[1, 2, 3]], dim=1), axis=[1]).eval(), a) 166 batched_mat = tf.expand_dims(mat, [0]) 169 self.assertAllEqual(result_batched, np.expand_dims(result, 0))
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | conv1d_test.py | 39 x = array_ops.expand_dims(x, 0) # Add batch dimension 40 x = array_ops.expand_dims(x, 2) # And depth dimension 42 filters = array_ops.expand_dims(filters, 1) # in_channels 43 filters = array_ops.expand_dims(filters, 2) # out_channels
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D | attention_ops_test.py | 60 array_ops.expand_dims(array_ops.expand_dims(t_rows, 0), 3), 74 array_ops.expand_dims(array_ops.expand_dims(t_cols, 0), 3),
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D | normalize_op_test.py | 43 norm = np.expand_dims(norm, d) 46 norm = np.expand_dims(norm, d) 54 return x / np.expand_dims(norm, axis)
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D | shape_ops_test.py | 178 np_ans = np.expand_dims(x, axis=dim) 180 tensor = array_ops.expand_dims(x, dim) 235 self.assertRaises(ValueError, array_ops.expand_dims, 237 self.assertRaises(ValueError, array_ops.expand_dims, 239 self.assertRaises(ValueError, array_ops.expand_dims, 241 self.assertRaises(ValueError, array_ops.expand_dims, 249 squeezed = array_ops.expand_dims(inp, 1) 259 self.assertAllEqual([7], array_ops.expand_dims(inp, 0).eval()) 260 self.assertAllEqual([7], array_ops.expand_dims(inp, -1).eval()) 263 self.assertAllEqual([True], array_ops.expand_dims(inp, 0).eval()) [all …]
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D | draw_bounding_box_op_test.py | 87 bboxes = array_ops.expand_dims(bboxes, 0) 90 image = array_ops.expand_dims(image, 0)
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D | aggregate_ops_test.py | 67 [np.expand_dims(d, 0) for d in data]), axis=0) 80 expected = np.sum(np.vstack([np.expand_dims(data, 0)] * count),
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D | matrix_square_root_op_test.py | 52 [np.expand_dims(matrix1, 0), 53 np.expand_dims(matrix2, 0)])
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/external/tensorflow/tensorflow/python/keras/utils/ |
D | kernelized_utils.py | 32 return array_ops.expand_dims(u, 0) 48 array_ops.expand_dims(x_matrix, 1), [1, y_shape[0], 1]) 50 array_ops.expand_dims(y_matrix, 0), [x_shape[0], 1, 1])
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D | metrics_utils.py | 371 predictions_extra_dim = array_ops.expand_dims(y_pred, 0) 372 labels_extra_dim = array_ops.expand_dims( 413 label_weights = array_ops.expand_dims(label_weights, 0) 522 mask = array_ops.expand_dims(tmp, -1) 529 flat_values.append(array_ops.expand_dims(tmp, -1))
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/external/tensorflow/tensorflow/python/ops/ |
D | ctc_ops.py | 494 array_ops.expand_dims(indices, 0), [batch_size, 1, 1]) 495 batch_idx = array_ops.expand_dims(math_ops.range(batch_size), 1) * [1, 0, 0] 496 indices += array_ops.expand_dims(batch_idx, 1) 502 return array_ops.expand_dims(trans, 0) + label_to_label 552 one_hot = array_ops.expand_dims(one_hot, axis=0) 553 ilabel_log_probs = array_ops.expand_dims(ilabel_log_probs, axis=2) 572 one_hot = array_ops.expand_dims(one_hot, axis=0) 573 label_states = array_ops.expand_dims(label_states, axis=3) 597 indices = unique_y + array_ops.expand_dims(batch_offset, axis=-1) 1081 indices=array_ops.expand_dims( [all …]
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D | init_ops.py | 654 array_ops.expand_dims(q, 0), shape) 658 array_ops.expand_dims(q, 0), shape) 662 array_ops.expand_dims(q, 0), shape) 865 return array_ops.expand_dims(array_ops.expand_dims(orth, 0), 0) 993 return array_ops.expand_dims(orth, 0) 1149 return array_ops.expand_dims( 1150 array_ops.expand_dims(array_ops.expand_dims(orth, 0), 0), 0)
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D | weights_broadcast_ops.py | 36 values_shape_2d = array_ops.expand_dims(values_shape, -1) 39 weights_shape_2d = array_ops.expand_dims(weights_shape, -1)
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D | nn_grad.py | 512 vec = array_ops.expand_dims(vec, -1) 543 array_ops.expand_dims(grad_grad, 1), 544 array_ops.expand_dims(softmax, 2)), 1101 array_ops.expand_dims( 1111 array_ops.expand_dims(ind, -1), array_ops.reshape(grad, [-1]), 1136 math_ops.equal(array_ops.expand_dims(output, -1), input), grad.dtype) 1138 grad = array_ops.expand_dims(grad, -1) 1139 num_selected = array_ops.expand_dims(math_ops.reduce_sum(indicators, -1), -1)
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/external/tensorflow/tensorflow/lite/kernels/ |
D | expand_dims.cc | 30 namespace expand_dims { namespace 113 static TfLiteRegistration r = {nullptr, nullptr, expand_dims::Prepare, in Register_EXPAND_DIMS() 114 expand_dims::Eval}; in Register_EXPAND_DIMS()
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | dense_attention.py | 147 v_mask = array_ops.expand_dims(v_mask, axis=-2) 165 q_mask = array_ops.expand_dims(q_mask, axis=-1) 473 q_reshaped = array_ops.expand_dims(query, axis=-2) 475 k_reshaped = array_ops.expand_dims(key, axis=-3)
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D | merge.py | 134 x = array_ops.expand_dims(x, axis=1) 148 array_ops.expand_dims(batch_size, axis=-1)]) 173 array_ops.expand_dims(batch_size, axis=-1), y_shape[:y_ndim - 1] 216 masks = [array_ops.expand_dims(m, axis=0) for m in mask if m is not None] 560 masks.append(array_ops.expand_dims(mask_i, axis=-1))
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/external/tensorflow/tensorflow/examples/wav_to_spectrogram/ |
D | wav_to_spectrogram.cc | 69 Output expand_dims = in WavToSpectrogram() local 71 Output squeeze = Squeeze(root.WithOpName("squeeze"), expand_dims, in WavToSpectrogram()
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/external/tensorflow/tensorflow/compiler/tests/ |
D | matrix_inverse_op_test.py | 57 [np.expand_dims(matrix1, 0), 58 np.expand_dims(matrix2, 0)])
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/external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
D | not_supported.txt | 133 expand_dims/expand_dims_axis_value=0,constant_axis=True,input_shape=[5,4],input_type=tf.float32 134 expand_dims/expand_dims_axis_value=1,constant_axis=True,input_shape=[5,4],input_type=tf.float32 135 expand_dims/expand_dims_axis_value=2,constant_axis=True,input_shape=[5,4],input_type=tf.float32 136 expand_dims/expand_dims_axis_value=-1,constant_axis=True,input_shape=[5,4],input_type=tf.float32 137 expand_dims/expand_dims_axis_value=-2,constant_axis=True,input_shape=[5,4],input_type=tf.float32 138 expand_dims/expand_dims_axis_value=-3,constant_axis=True,input_shape=[5,4],input_type=tf.float32 139 expand_dims/expand_dims_axis_value=0,constant_axis=False,input_shape=[5,4],input_type=tf.float32 140 expand_dims/expand_dims_axis_value=1,constant_axis=False,input_shape=[5,4],input_type=tf.float32 141 expand_dims/expand_dims_axis_value=2,constant_axis=False,input_shape=[5,4],input_type=tf.float32 142 expand_dims/expand_dims_axis_value=-1,constant_axis=False,input_shape=[5,4],input_type=tf.float32 [all …]
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/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_where_op.py | 154 array_ops.expand_dims(selected_rows, 1), 155 array_ops.expand_dims(selected_cols, 1), selected_coords[:, 1:]
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/external/tensorflow/tensorflow/examples/speech_commands/ |
D | input_data.py | 435 'spectrogram', tf.expand_dims(spectrogram, -1), max_outputs=1) 446 input=tf.expand_dims(spectrogram, -1), 460 'mfcc', tf.expand_dims(self.output_, -1), max_outputs=1) 484 tf.expand_dims(tf.expand_dims(self.output_, -1), 0),
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/external/tensorflow/tensorflow/python/kernel_tests/signal/ |
D | shape_ops_test.py | 41 tensor = array_ops.expand_dims(tensor, 0) 48 expected = np.expand_dims(expected, axis=0) 54 tensor = array_ops.expand_dims(tensor, 0) 63 expected = np.expand_dims(expected, axis=0)
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/external/tensorflow/tensorflow/python/ops/signal/ |
D | dct_ops.py | 141 _array_ops.expand_dims(n1, 0), [[0, axis_dim - 1]], 153 _array_ops.expand_dims(n1, 0), [[0, axis_dim - 1]],
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