| /external/tensorflow/tensorflow/core/framework/ |
| tensor_shape.h | 169 /// REQUIRES: `dim_sizes[i] >= 0` (or >= -1 for PartialTensorShape)
170 explicit TensorShapeBase(gtl::ArraySlice<int64> dim_sizes);
171 TensorShapeBase(std::initializer_list<int64> dim_sizes)
172 : TensorShapeBase(gtl::ArraySlice<int64>(dim_sizes)) {}
244 gtl::InlinedVector<int64, 4> dim_sizes() const;
259 void InitDims(gtl::ArraySlice<int64> dim_sizes);
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| tensor_shape_test.cc | 219 /// REQUIRES: `dim_sizes[i] >= 0`
220 explicit TensorShapeOld(gtl::ArraySlice<int64> dim_sizes);
221 TensorShapeOld(std::initializer_list<int64> dim_sizes)
222 : TensorShapeOld(gtl::ArraySlice<int64>(dim_sizes)) {}
276 gtl::ArraySlice<int64> dim_sizes() const { return dim_sizes_; } function in class:tensorflow::__anon45008::TensorShapeOld
390 TensorShapeOld::TensorShapeOld(gtl::ArraySlice<int64> dim_sizes) {
391 dim_sizes_.reserve(dim_sizes.size());
393 for (auto s : dim_sizes) {
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| tensor.h | 750 CHECK_EQ(sizeof(T), shape_.dim_sizes()[NDIMS] * DataTypeSize(dtype()));
753 dims[d] = shape_.dim_sizes()[d];
766 CHECK_EQ(sizeof(T), shape_.dim_sizes()[NDIMS] * DataTypeSize(dtype()));
769 dims[d] = shape_.dim_sizes()[d];
[all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| resampler_ops.cc | 59 auto warp_dims = warp_shape.dim_sizes();
256 auto warp_dims = warp_shape.dim_sizes();
363 auto warp_dims = warp_shape.dim_sizes();
499 for (int size : warp_shape.dim_sizes()) {
579 auto warp_dims = warp_shape.dim_sizes();
620 for (int size : warp_shape.dim_sizes()) {
665 auto warp_dims = warp_shape.dim_sizes();
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| cross_op.cc | 52 for (auto dim_size : in0_shape.dim_sizes()) {
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| scatter_nd_op.cc | 108 buffer_shape.dim_sizes());
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| tensor_list_utils.cc | 94 buffer_shape.dim_sizes());
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| stack_ops.cc | 154 auto update = xla::Reshape(value, slice_shape.dim_sizes());
208 auto slice_shape = stack_shape.dim_sizes();
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| fft_ops.cc | 61 absl::InlinedVector<int64, 4> slice_sizes = input_shape.dim_sizes();
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| reverse_sequence_op.cc | 117 auto slice_sizes = input_shape.dim_sizes();
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| segment_reduction_ops.cc | 81 xla::Broadcast(InitialValue(builder), buffer_shape.dim_sizes());
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| fake_quantize_ops.cc | 170 gradient_shape.dim_sizes());
256 xla::XlaOp zeroes = xla::Broadcast(zero, gradient_shape.dim_sizes());
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| strided_slice_op.cc | 101 slice = xla::Reshape(slice, final_shape.dim_sizes());
175 grad = xla::Reshape(grad, processing_shape.dim_sizes());
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| ragged_tensor_shape.py | 132 def from_dim_sizes(dim_sizes):
140 dim_sizes: List of int64 scalars or vectors.
146 [dim_sizes]):
147 dim_sizes = tuple(
149 size, dtype=dtypes.int64, name='dim_sizes') for size in dim_sizes)
152 for dim, dim_size in enumerate(dim_sizes):
157 return RaggedTensorDynamicShape(dim_sizes[:inner_split],
158 dim_sizes[inner_split:])
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| /external/tensorflow/tensorflow/core/kernels/ |
| batchtospace_op.cc | 192 internal_output_shape.dim_sizes()), \
195 internal_input_shape.dim_sizes())))); \
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| spacetobatch_op.cc | 193 internal_input_shape.dim_sizes()), \
196 internal_output_shape.dim_sizes()))); \
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| strided_slice_op_impl.h | 87 gtl::InlinedVector<int64, 4> processing_dims = processing_shape.dim_sizes();
123 gtl::InlinedVector<int64, 4> processing_dims = processing_shape.dim_sizes();
146 gtl::InlinedVector<int64, 4> processing_dims = processing_shape.dim_sizes();
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| sparse_to_dense_op.cc | 102 indices.shaped<Index, 2>(ix_shape.dim_sizes()).template cast<int64>();
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| shape_ops.h | 154 auto existing_dims = ctx->input(0).shape().dim_sizes();
200 auto existing_dims = ctx->input(0).shape().dim_sizes();
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| /external/tensorflow/tensorflow/core/kernels/data/ |
| concatenate_dataset_op.cc | 195 auto dims1 = ts1.dim_sizes();
196 auto dims2 = ts2.dim_sizes();
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| tensor_dataset_op.cc | 53 shapes_.emplace_back(t.shape().dim_sizes());
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| /external/tensorflow/tensorflow/core/kernels/hexagon/ |
| graph_transfer_utils.cc | 76 for (const int64 dim : input.second.shape().dim_sizes()) {
92 for (const int64 dim : tensor_shape_type->second.dim_sizes()) {
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| /external/tensorflow/tensorflow/compiler/aot/ |
| codegen.cc | 131 string dim_sizes, indices; local
134 dim_sizes = "[1]";
139 dim_sizes += absl::StrCat("[", shape.dimensions(dim), "]");
146 rewrites->push_back({"{{DIM_SIZES}}", dim_sizes});
188 return (*static_cast<{{TYPE}}(*){{DIM_SIZES}}>(
195 return (*static_cast<const {{TYPE}}(*){{DIM_SIZES}}>(
231 return (*static_cast<{{TYPE}}(*){{DIM_SIZES}}>(
238 return (*static_cast<const {{TYPE}}(*){{DIM_SIZES}}>(
277 return (*static_cast<{{TYPE}}(*){{DIM_SIZES}}>(
[all...] |
| /external/tensorflow/tensorflow/core/kernels/data/experimental/ |
| directed_interleave_dataset_op.cc | 263 auto dims1 = ts1.dim_sizes();
264 auto dims2 = ts2.dim_sizes();
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| /external/tensorflow/tensorflow/core/ops/ |
| math_ops_test.cc | 219 auto shape_proto = [](std::initializer_list<int64> dim_sizes) {
221 for (auto i : dim_sizes) p.add_dim()->set_size(i);
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