| /external/tensorflow/tensorflow/python/ops/ |
| image_grad_test.py | 39 out_shape = [1, 4, 6, 1]
47 out_shape[1:3])
48 self.assertEqual(out_shape, list(resize_out.get_shape()))
51 self.assertEqual(out_shape, list(resize_out.shape))
56 out_shape = [1, 4, 6, 1]
64 out_shape[1:3])
66 input_tensor, in_shape, resize_out, out_shape, x_init_value=x)
72 out_shape = [1, 2, 3, 1]
80 out_shape[1:3])
82 input_tensor, in_shape, resize_out, out_shape, x_init_value=x
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| decode_raw_op.cc | 52 TensorShape out_shape = input.shape(); variable
54 out_shape.AddDim(0);
56 OP_REQUIRES_OK(context, context->allocate_output("output", out_shape,
66 out_shape.AddDim(added_dim);
69 context, context->allocate_output("output", out_shape, &output_tensor));
|
| diag_op.cc | 53 TensorShape out_shape; variable
55 out_shape.AddDim(diagonal.dim_size(i));
58 out_shape.AddDim(diagonal.dim_size(i));
62 context->allocate_output(0, out_shape, &output_tensor));
93 TensorShape out_shape; variable
95 out_shape.AddDim(tensor.dim_size(i));
99 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &output));
101 Status s = diagPartFunc(context, out_shape.num_elements(),
|
| nth_element_op.cc | 67 TensorShape out_shape; variable
69 out_shape.AddDim(input_in.dim_size(i));
73 context->allocate_output(0, out_shape, &output_tensor));
|
| determinant_op.cc | 149 TensorShape out_shape; variable
151 out_shape.AddDim(input.dim_size(dim));
153 out_shape.AppendShape(TensorShape({}));
155 OP_REQUIRES_OK_ASYNC(context, context->allocate_output(0, out_shape, &out),
289 TensorShape out_shape; variable
291 out_shape.AddDim(input.dim_size(dim));
293 out_shape.AppendShape(TensorShape({}));
295 OP_REQUIRES_OK_ASYNC(context, context->allocate_output(0, out_shape, &sign),
299 context, context->allocate_output(1, out_shape, &log_abs_det), done);
|
| extract_image_patches_op.cc | 97 TensorShape out_shape(out_sizes);
100 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &output));
103 if (out_shape.num_elements() == 0) {
|
| extract_volume_patches_op.cc | 124 TensorShape out_shape(out_sizes);
127 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &output));
130 if (out_shape.num_elements() == 0) {
|
| mkl_batch_matmul_op.cc | 68 TensorShape out_shape; variable
75 out_shape.AddDim(lhs.dim_size(i));
77 auto batch_size = (ndims == 2) ? 1 : out_shape.num_elements();
89 out_shape.AddDim(lhs_rows);
90 out_shape.AddDim(rhs_cols);
92 OP_REQUIRES_OK(ctx, ctx->allocate_output(0, out_shape, &out));
|
| reduction_ops_common.h | 89 // out = tmp_out.reshape(out_shape)
95 TensorShape out_shape() const;
164 if (!out.CopyFrom(data, helper.out_shape())) {
239 if (!out.CopyFrom(tmp_out, helper.out_shape())) {
|
| cudnn_pooling_gpu.cc | 42 const auto out_shape = output->shape(); local
65 ShapeFromFormat(FORMAT_NCHW, out_shape, data_format),
89 GetTensorDim(out_shape, data_format, '2' - i));
|
| depthwise_conv_op.cc | 355 TensorShape out_shape = variable
360 FastBoundsCheck(out_shape.num_elements(),
365 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &output));
368 if (out_shape.num_elements() == 0) {
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| mkl_matmul_op.cc | 72 TensorShape out_shape(
75 OP_REQUIRES_OK(ctx, ctx->allocate_output(0, out_shape, &out));
|
| quantized_matmul_op.cc | 117 TensorShape out_shape(
120 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &c));
|
| maxpooling_op.cc | 1155 TensorShape out_shape = variable
1273 TensorShape out_shape = variable
[all...] |
| /external/tensorflow/tensorflow/python/profiler/internal/ |
| flops_registry.py | 142 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
143 out_shape.assert_is_fully_defined()
144 return ops.OpStats("flops", out_shape.num_elements() * ops_per_element)
245 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
246 out_shape.assert_is_fully_defined()
248 + out_shape.num_elements() * (finalize_flops - reduce_flops))
317 out_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
318 out_shape.assert_is_fully_defined()
321 return ops.OpStats("flops", kernel_area * out_shape.num_elements())
397 # out_shape = [batch_size, image_y_dim, image_x_dim, input_depth
[all...] |
| /external/tensorflow/tensorflow/core/ops/ |
| batch_ops.cc | 84 shape_inference::ShapeHandle out_shape;
86 c->ReplaceDim(c->input(0), 0, c->UnknownDim(), &out_shape));
87 c->set_output(0, out_shape);
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| gather_op.cc | 73 TensorShape out_shape; local
74 out_shape.AppendShape(input_shape_pre_axis);
75 out_shape.AppendShape(indices_shape_no_index_vectors);
76 out_shape.AppendShape(input_shape_post_axis);
79 xla::Broadcast(XlaHelpers::Zero(builder, dtype), out_shape.dim_sizes());
|
| /external/tensorflow/tensorflow/core/kernels/neon/ |
| neon_depthwise_conv_op.cc | 97 TensorShape out_shape({batch, out_rows, out_cols, out_depth});
100 FastBoundsCheck(out_shape.num_elements(),
107 OP_REQUIRES_OK(context, context->allocate_output(0, out_shape, &output));
118 if (out_shape.num_elements() == 0) {
138 output_ptr, ToNeonDims(out_shape));
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| cudnn_determinism_test.py | 63 out_shape = conv_op.get_shape()
64 out_op = self._random_data_op(out_shape)
|
| extract_image_patches_grad_test.py | 99 out_shape = out_val.get_shape().as_list()
102 out_val, out_shape)
|
| extract_volume_patches_grad_test.py | 76 out_shape = out_val.get_shape().as_list()
79 out_val, out_shape)
|
| unstack_op_test.py | 97 out_shape = list(shape)
98 del out_shape[1]
104 out_shape)
|
| morphological_ops_test.py | 220 out_shape = self.evaluate(out_tensor).shape
226 out_shape, [image_init, kernel_init],
496 out_shape = self.evaluate(out_tensor).shape
502 out_shape, [image_init, kernel_init],
|
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| merge_reshape_into_preceding_transpose.cc | 67 std::vector<int> out_shape = output_array.shape().dims(); local
86 for (const auto val : out_shape) {
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| data_feeder.py | 71 def out_el_shape(out_shape, num_classes):
72 out_shape = list(out_shape[1:]) if len(out_shape) > 1 else []
74 if out_shape and out_shape[0] == 1:
75 out_shape = out_shape[1:]
77 return [batch_size] + out_shape + [num_classes]
79 return [batch_size] + out_shape
[all...] |
