| /external/tensorflow/tensorflow/python/keras/layers/ |
| core_test.py | 260 keras.layers.Reshape,
265 keras.layers.Reshape,
270 keras.layers.Reshape,
275 keras.layers.Reshape,
305 target_outputs = np.reshape(
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| core.py | 370 @keras_export('keras.layers.Reshape')
371 class Reshape(Layer):
392 model.add(Reshape((3, 4), input_shape=(12,)))
397 model.add(Reshape((6, 2)))
401 model.add(Reshape((-1, 2, 2)))
407 super(Reshape, self).__init__(**kwargs)
465 return array_ops.reshape(inputs,
470 base_config = super(Reshape, self).get_config()
578 outputs = array_ops.reshape(
[all...] |
| /external/tensorflow/tensorflow/python/tools/ |
| print_selective_registration_header_test.py | 37 op: "Reshape"
118 ('Reshape', 'ReshapeOp'), #
136 ('Reshape', 'ReshapeOp'), #
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| /external/tensorflow/tensorflow/compiler/xla/client/ |
| xla_builder_test.cc | 267 // | reshape: f32[1,2]
274 op::Broadcast(op::Reshape(op::Parameter(1)))));
286 // reshape and a broadcast.
292 // broadcast: f32[2,3,4] reshape: f32[2,4]
299 op::Broadcast(op::Reshape(op::Parameter(1)))));
319 op::Broadcast(op::Reshape(op::Broadcast())));
339 Reshape(x, /*new_sizes=*/{6, 35});
342 EXPECT_THAT(root, op::Reshape(op::Parameter()));
348 Reshape(x, /*dimensions=*/{3, 2, 1, 0}, /*new_sizes=*/{6, 35});
351 EXPECT_THAT(root, op::Reshape(op::Transpose(op::Parameter())))
[all...] |
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| reshape.py | 15 """Reshape bijectors."""
37 "Reshape",
65 class Reshape(bijector.Bijector):
68 The semantics generally follow that of `tf.reshape()`, with
75 * The `Reshape` bijector automatically broadcasts over the leftmost
78 number of dimensions to reshape is inferred from the provided
87 r = tfb.Reshape(event_shape_out=[1, -1])
118 """Creates a `Reshape` bijector.
138 with ops.name_scope(name, "reshape",
158 super(Reshape, self).__init__
[all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| image_ops.cc | 373 active_elem = xla::Reshape(active_elem, {});
386 row_iou = xla::Reshape(row_iou, {num_boxes});
459 const xla::XlaOp c_y0 = xla::Reshape(xla::SliceInDim(boxes_sorted,
465 const xla::XlaOp c_x0 = xla::Reshape(xla::SliceInDim(boxes_sorted,
471 const xla::XlaOp c_y1 = xla::Reshape(xla::SliceInDim(boxes_sorted,
477 const xla::XlaOp c_x1 = xla::Reshape(xla::SliceInDim(boxes_sorted,
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| resampler_ops.cc | 261 // Reshape the last dimension of size 4 to two dimensions [2, 2].
267 auto reshaped_weights = xla::Reshape(weights, /*dimensions=*/reshape_dims,
466 // Reshape before concatenating with y values.
467 XlaOp reshaped_x = xla::Reshape(x_result, reshaped_dims, reshaped_sizes);
477 XlaOp reshaped_y = xla::Reshape(y_result, reshaped_dims, reshaped_sizes);
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| concat_op.cc | 85 input_data.push_back(xla::Reshape(handle, {1}));
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| dynamic_stitch_op.cc | 166 input[input_num] = xla::Reshape(handle, new_shape.dim_sizes());
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| extract_image_patches_op.cc | 100 // eye = np.eye(kH * kW * D).reshape([kH, kW, D, kH * kW * kD])
113 // filter = np.equal(np.reshape(iota, [-1, 1]), iota).astype(np.float32)
116 auto lhs = xla::Reshape(iota, lhs_shape);
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| conv_op_helpers.cc | 135 // Create a [H, W, ..., 1, N*M] reshape of the filter.
140 return xla::Reshape(
154 return xla::Reshape(
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| random_ops.cc | 171 auto swap_index = xla::Reshape(
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| algebraic_simplifier_test.cc | 1574 HloInstruction* reshape = local
1579 HloOpcode::kCopy, reshape)); local
1945 HloInstruction* reshape = local
3553 HloInstruction* reshape = builder.AddInstruction( local
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| convolution_variants_test.cc | [all...] |
| slice_test.cc | 174 auto reshape = Reshape(original, {24, 3, 2, 7}); local
175 Slice(reshape, {0, 0, 0, 0}, {11, 3, 2, 7}, {1, 1, 1, 1});
184 auto reshape = Reshape(original, {2 * 3 * 5, 7}); local
185 Slice(reshape, {0, 0}, {4, 7}, {1, 1});
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| dot_operation_test.cc | 558 auto x_flat = Reshape(x, {0, 1, 2, 3}, {4, 2, 2});
559 auto y_flat = Reshape(y, {0, 1, 2, 3}, {4, 2, 2});
564 // Slice off individual matrices and reshape to 2D tensors.
566 x_slice = Reshape(x_slice, {0, 1, 2}, {2, 2});
568 y_slice = Reshape(y_slice, {0, 1, 2}, {2, 2});
571 out = Reshape(out, {0, 1}, {1, 2, 2});
575 Reshape(out_flat, {0, 1, 2}, {2, 2, 2, 2});
[all...] |
| /external/tensorflow/tensorflow/tools/graph_transforms/ |
| quantize_nodes_test.cc | 106 // Reshape is not included here because it can be added as part of the
480 Reshape(root.WithOpName("reshape_op"), constant_op, {10, 2});
523 Output dequantize_reshape = Reshape(root.WithOpName("dequantize_reshape"),
622 Output dequantize_reshape = Reshape(root.WithOpName("dequantize_reshape"),
748 Output dequantize_reshape = Reshape(root.WithOpName("dequantize_reshape"),
[all...] |
| /external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
| mnist_eager_multigpu.py | 52 tf.keras.layers.Reshape(
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| mnist_tf1_tpu.py | 50 tf.keras.layers.Reshape(
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| /external/tensorflow/tensorflow/contrib/specs/python/ |
| specs_ops.py | 111 Reshape = Fun(array_ops.reshape)
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| /external/tensorflow/tensorflow/core/grappler/optimizers/data/vectorization/ |
| cwise_op_vectorizer.cc | 34 // To avoid that, we reshape stacked inputs to the maximum rank they need
103 Output reshaped = ops::Reshape(scope, input, new_shape);
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| /external/tensorflow/tensorflow/core/common_runtime/ |
| function_test.cc | [all...] |
| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| slicing.cc | 147 to_concat.push_back(Reshape(index, index_shape.dimensions()));
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| /external/tensorflow/tensorflow/core/kernels/ |
| deserialize_sparse_string_op.cc | 77 // motion in the Concat and Reshape.
193 // Compute the input shape for the reshape operation.
198 // Compute the target shape for the reshape operation.
207 Reshape(context, output.indices(), input_shape, target_shape,
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| /external/tensorflow/tensorflow/examples/tf2_showcase/ |
| mnist.py | 91 l.Reshape(
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