Searched refs:num_spatial_dims (Results 1 - 25 of 25) sorted by relevance

/external/tensorflow/tensorflow/core/util/
H A Dtensor_format_test.cc105 GetTensorDimMap(const int num_spatial_dims, const TensorFormat format) { argument
107 (format == FORMAT_NHWC) ? DimMaps::kTdmNHWC[num_spatial_dims] :
109 format == FORMAT_NCHW_VECT_C) ? DimMaps::kTdmNCHW[num_spatial_dims]
114 GetFilterDimMap(const int num_spatial_dims, argument
117 (format == FORMAT_HWIO) ? DimMaps::kFdmHWIO[num_spatial_dims] :
119 format == FORMAT_OIHW_VECT_I) ? DimMaps::kFdmOIHW[num_spatial_dims]
155 template <int num_spatial_dims>
159 auto& tdm = GetTensorDimMap(num_spatial_dims, format);
160 int num_dims = GetTensorDimsFromSpatialDims(num_spatial_dims, format);
161 LOG(INFO) << ToString(format) << ", num_spatial_dims
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H A Dtensor_format.h107 // Returns the rank of a tensor with 'num_spatial_dims' spatial dimensions and
109 inline int GetTensorDimsFromSpatialDims(int num_spatial_dims, argument
112 return num_spatial_dims + 3; // Include N,C,InnerC.
114 return num_spatial_dims + 2; // Include N,C.
118 // Returns the rank of a tensor with 'num_spatial_dims' spatial dimensions and
120 inline int GetFilterTensorDimsFromSpatialDims(int num_spatial_dims, argument
123 return num_spatial_dims + 3; // Include O,I,InnerI.
125 return num_spatial_dims + 2; // Include O,I.
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
H A Ddepthtospace_op.cc57 int num_spatial_dims = GetTensorSpatialDims(input_rank, data_format_); variable
67 for (int i = 0; i < num_spatial_dims; ++i) {
71 for (int i = 0; i < num_spatial_dims; ++i) {
78 for (int i = 0; i < num_spatial_dims; ++i) {
80 transpose_order.push_back(i + 1 + num_spatial_dims);
82 transpose_order.push_back(feature_dim + num_spatial_dims);
85 for (int i = 0; i < num_spatial_dims; ++i) {
93 for (int i = 0; i < num_spatial_dims; ++i) {
98 for (int i = 0; i < num_spatial_dims; ++i) {
103 transpose_order.push_back(1 + num_spatial_dims);
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H A Dspacetodepth_op.cc57 int num_spatial_dims = GetTensorSpatialDims(input_rank, data_format_); variable
67 for (int i = 0; i < num_spatial_dims; ++i) {
76 for (int i = 0; i < num_spatial_dims; ++i) {
83 for (int i = 0; i < num_spatial_dims; ++i) {
86 for (int i = 0; i < num_spatial_dims; ++i) {
89 transpose_order.push_back(feature_dim + num_spatial_dims);
92 for (int i = 0; i < num_spatial_dims; ++i) {
99 for (int i = 0; i < num_spatial_dims; ++i) {
109 for (int i = 0; i < num_spatial_dims; ++i) {
115 for (int i = 0; i < num_spatial_dims;
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H A Dimage_resize_ops.cc79 int num_spatial_dims = in_size.size(); local
81 dims.kernel_size.resize(num_spatial_dims);
82 dims.stride.resize(num_spatial_dims);
83 for (int i = 0; i < num_spatial_dims; ++i) {
144 const int num_spatial_dims, std::vector<int64> in_size,
161 for (int i = 0; i < num_spatial_dims; ++i) {
166 dimension_numbers.set_kernel_input_feature_dimension(num_spatial_dims);
167 dimension_numbers.set_kernel_output_feature_dimension(num_spatial_dims + 1);
183 for (int i = 0; i < num_spatial_dims; ++i) {
194 const int num_spatial_dims, st
142 ResizeUsingDilationAndConvolution( xla::ComputationBuilder* builder, const xla::ComputationDataHandle& input, const int num_spatial_dims, std::vector<int64> in_size, std::vector<int64> out_size, const int64 channels) argument
192 ResizeUsingDilationAndConvolutionGradOp( xla::ComputationBuilder* builder, const xla::ComputationDataHandle& grad, const int num_spatial_dims, std::vector<int64> in_size, std::vector<int64> grad_size, const int64 channels) argument
284 const int num_spatial_dims = 2; variable
407 const int num_spatial_dims = 2; variable
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H A Dextract_image_patches_op.cc42 const int num_spatial_dims = num_dims - 2; variable
69 for (int i = 0; i < num_spatial_dims; ++i) {
102 for (int i = 0; i < num_spatial_dims; ++i) {
107 lhs_shape[num_spatial_dims] = depth;
108 lhs_shape[num_spatial_dims + 1] = 1;
119 builder->Eq(lhs, iota, {num_spatial_dims + 1}), type);
122 std::vector<int64> window_strides(num_spatial_dims);
123 std::vector<int64> lhs_dilation(num_spatial_dims, 1);
124 std::vector<int64> rhs_dilation(num_spatial_dims);
125 std::vector<std::pair<int64, int64>> padding(num_spatial_dims);
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H A Dpooling_ops.cc38 PoolingOp(OpKernelConstruction* ctx, int num_spatial_dims) argument
39 : XlaOpKernel(ctx), num_spatial_dims_(num_spatial_dims) {
131 MaxPoolOp(OpKernelConstruction* ctx, int num_spatial_dims) argument
132 : PoolingOp(ctx, /*num_spatial_dims=*/num_spatial_dims) {}
154 : MaxPoolOp(ctx, /*num_spatial_dims=*/2) {
170 : MaxPoolOp(ctx, /*num_spatial_dims=*/3) {}
181 int num_spatial_dims, TensorFormat data_format) {
199 std::vector<int64> input_dim_sizes(num_spatial_dims);
200 std::vector<int64> window_dims(num_spatial_dims);
177 AvgPoolDivideByCount( XlaOpKernelContext* ctx, const xla::ComputationDataHandle& output, DataType dtype, const TensorShape& input_shape, xla::Padding padding, const std::vector<int64>& ksize, const std::vector<int64>& stride, int num_spatial_dims, TensorFormat data_format) argument
228 AvgPoolOp(OpKernelConstruction* ctx, int num_spatial_dims) argument
277 MaxPoolGradOp(OpKernelConstruction* ctx, int num_spatial_dims) argument
388 AvgPoolGradOp(OpKernelConstruction* ctx, int num_spatial_dims) argument
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H A Dconv_ops.cc177 explicit ConvOp(OpKernelConstruction* ctx, int num_spatial_dims, argument
180 num_spatial_dims_(num_spatial_dims),
308 : ConvOp(ctx, /*num_spatial_dims=*/2, /*depthwise=*/false) {}
315 : ConvOp(ctx, /*num_spatial_dims=*/3, /*depthwise=*/false) {}
322 : ConvOp(ctx, /*num_spatial_dims=*/2, /*depthwise=*/true) {}
329 explicit ConvBackpropInputOp(OpKernelConstruction* ctx, int num_spatial_dims, argument
332 num_spatial_dims_(num_spatial_dims),
461 : ConvBackpropInputOp(ctx, /*num_spatial_dims=*/2, /*depthwise=*/false) {}
470 : ConvBackpropInputOp(ctx, /*num_spatial_dims=*/3, /*depthwise=*/false) {}
479 : ConvBackpropInputOp(ctx, /*num_spatial_dims
487 ConvBackpropFilterOp(OpKernelConstruction* ctx, int num_spatial_dims, bool depthwise) argument
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/external/tensorflow/tensorflow/compiler/xla/service/cpu/
H A Dir_emission_utils.cc55 const int64 num_spatial_dims = dnums.output_spatial_dimensions_size(); local
56 if (num_spatial_dims > 2) {
60 for (int64 i = 0; i < num_spatial_dims; ++i) {
H A Dconv_canonicalization.cc44 const int64 num_spatial_dims = dnums.output_spatial_dimensions_size(); local
45 const int64 num_dims = num_spatial_dims + 2;
62 for (int64 i = 0; i < num_spatial_dims; ++i) {
81 for (int64 i = 0; i < num_spatial_dims; ++i) {
105 for (int64 i = 0; i < num_spatial_dims; ++i) {
118 for (int64 i = 0; i < num_spatial_dims; ++i) {
H A Dir_emitter.cc1002 int num_spatial_dims = dnums.output_spatial_dimensions_size();
1003 std::vector<llvm::Value*> output_spatial(num_spatial_dims);
1004 for (int i = 0; i < num_spatial_dims; ++i) {
1021 std::vector<llvm::Value*> kernel_spatial(num_spatial_dims);
1022 for (int i = 0; i < num_spatial_dims; ++i) {
1055 std::vector<llvm::Value*> input_spatial(num_spatial_dims);
1056 for (int i = 0; i < num_spatial_dims; ++i) {
1077 for (int i = 0; i < num_spatial_dims; ++i) {
1099 for (int i = 0; i < num_spatial_dims; ++i) {
1109 int num_dims = num_spatial_dims
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/external/tensorflow/tensorflow/contrib/fused_conv/ops/
H A Dfused_conv2d_bias_activation_op.cc63 constexpr int num_spatial_dims = 2;
65 GetTensorDimsFromSpatialDims(num_spatial_dims, data_format);
71 GetFilterDimIndex<num_spatial_dims>(filter_format, 'O'));
/external/tensorflow/tensorflow/python/ops/
H A Dnn_ops.py225 op(input, num_spatial_dims, padding)
231 num_spatial_dims,
244 `[num_spatial_dims, 2]` based on the value of `padding` and the spatial
297 def combined_op(converted_input, num_spatial_dims, _):
298 result = op_1(converted_input, num_spatial_dims, "VALID")
300 result = op_k(result, num_spatial_dims, "VALID")
317 def combined_op(converted_input, num_spatial_dims, _):
318 result = op_1(converted_input, num_spatial_dims, "SAME")
320 result = op_k(result, num_spatial_dims, "SAME")
326 dilation_rate: int32 Tensor of *known* shape [num_spatial_dims]
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/external/tensorflow/tensorflow/core/kernels/
H A Dconv_grad_ops.cc98 StringPiece label, int num_spatial_dims, const TensorShape& input_shape,
103 const int num_dims = num_spatial_dims + 2;
140 dims->spatial_dims.resize(num_spatial_dims);
141 for (int i = 0; i < num_spatial_dims; ++i) {
150 Status ConvBackpropComputeDimensions(StringPiece label, int num_spatial_dims, argument
159 label, num_spatial_dims, input_shape, filter_shape, out_backprop_shape,
97 ConvBackpropComputeDimensionsV2( StringPiece label, int num_spatial_dims, const TensorShape& input_shape, const TensorShape& filter_shape, const TensorShape& out_backprop_shape, const gtl::ArraySlice<int32>& dilations, const std::vector<int32>& strides, Padding padding, TensorFormat data_format, ConvBackpropDimensions* dims) argument
H A Dconv_grad_ops.h242 Status ConvBackpropComputeDimensions(StringPiece label, int num_spatial_dims,
253 StringPiece label, int num_spatial_dims, const TensorShape& input_shape,
/external/tensorflow/tensorflow/core/framework/
H A Dcommon_shape_fns.cc391 constexpr int num_spatial_dims = 2; local
392 const int rank = GetTensorDimsFromSpatialDims(num_spatial_dims, data_format);
437 filter_shape, GetFilterDimIndex<num_spatial_dims>(filter_format, 'O'));
439 filter_shape, GetFilterDimIndex<num_spatial_dims>(filter_format, 'H'));
441 filter_shape, GetFilterDimIndex<num_spatial_dims>(filter_format, 'W'));
446 GetFilterDimIndex<num_spatial_dims>(filter_format, 'I')),
452 filter_shape, GetFilterDimIndex<num_spatial_dims>(filter_format, 'I'));
665 constexpr int num_spatial_dims = 2; local
667 input_shape, GetTensorDimIndex<num_spatial_dims>(data_format, 'N'));
669 input_shape, GetTensorDimIndex<num_spatial_dims>(data_forma
817 constexpr int num_spatial_dims = 2; local
919 constexpr int num_spatial_dims = 2; local
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/external/tensorflow/tensorflow/python/kernel_tests/
H A Datrous_convolution_test.py52 num_spatial_dims = len(rate)
53 spatial_shape = np.array(filters.shape[:num_spatial_dims])
57 output[tuple(np.s_[::rate[i]] for i in range(num_spatial_dims))] = filters
219 def combined_op(converted_input, num_spatial_dims, padding_arg): # pylint: disable=unused-argument
/external/tensorflow/tensorflow/compiler/xla/service/
H A Dshape_inference.cc1611 const int num_spatial_dims = dnums.input_spatial_dimensions_size(); local
1612 if (window.dimensions_size() != num_spatial_dims) {
1619 const int num_dims = num_spatial_dims + 2;
1689 std::vector<int64> input_spatial_dims(num_spatial_dims);
1690 for (int i = 0; i < num_spatial_dims; ++i) {
1696 std::vector<int64> kernel_spatial_dims(num_spatial_dims);
1697 for (int i = 0; i < num_spatial_dims; ++i) {
1714 std::vector<int64> window_dims(num_spatial_dims);
1715 for (int i = 0; i < num_spatial_dims; ++i) {
1738 for (int i = 0; i < num_spatial_dims;
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H A Dhlo_evaluator.cc903 const int64 num_spatial_dims = dnums.output_spatial_dimensions_size();
904 CHECK_EQ(num_spatial_dims, dnums.input_spatial_dimensions_size());
905 CHECK_EQ(num_spatial_dims, dnums.kernel_spatial_dimensions_size());
906 CHECK_GE(num_spatial_dims, 0);
907 CHECK_EQ(window.dimensions_size(), num_spatial_dims);
912 CHECK_EQ(num_spatial_dims + 2, lhs_rank);
913 CHECK_EQ(num_spatial_dims + 2, rhs_rank);
/external/tensorflow/tensorflow/core/ops/
H A Darray_ops.cc2178 constexpr int num_spatial_dims = 2;
2180 GetTensorDimsFromSpatialDims(num_spatial_dims, data_format);
2188 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_format, 'N'));
2190 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_format, 'H'));
2192 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_format, 'W'));
2194 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_format, 'C'));
2232 constexpr int num_spatial_dims = 2;
2234 GetTensorDimsFromSpatialDims(num_spatial_dims, data_format);
2243 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_format, 'N'));
2245 c->Dim(input, GetTensorDimIndex<num_spatial_dims>(data_forma
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/external/tensorflow/tensorflow/compiler/xla/client/
H A Dcomputation_builder.cc594 int num_spatial_dims = num_dims - 2; local
600 if (numbers.size() != num_spatial_dims) {
602 num_spatial_dims, field_name,
1513 ComputationBuilder::CreateDefaultConvDimensionNumbers(int num_spatial_dims) { argument
1523 for (int i = 0; i < num_spatial_dims; ++i) {
H A Dcomputation_builder.h366 int num_spatial_dims = 2);
/external/tensorflow/tensorflow/compiler/xla/python/
H A Dxla_client.py1070 def _GetConvDimensionNumbers(self, num_spatial_dims):
1072 nd = num_spatial_dims
/external/tensorflow/tensorflow/compiler/tests/
H A Drandomized_tests.cc311 WindowedSpatialDims ChooseWindowedSpatialDims(int num_spatial_dims);
576 int num_spatial_dims) {
580 d.kernel_dims.resize(num_spatial_dims);
581 d.input_dims.resize(num_spatial_dims);
582 d.output_dims.resize(num_spatial_dims);
583 d.stride_dims.resize(num_spatial_dims);
584 for (int i = 0; i < num_spatial_dims; ++i) {
575 ChooseWindowedSpatialDims( int num_spatial_dims) argument
/external/tensorflow/tensorflow/contrib/layers/python/layers/
H A Dlayers.py2375 num_spatial_dims = input_rank - 2
2378 window_shape=utils.n_positive_integers(num_spatial_dims, kernel_size),
2382 dilation_rate=utils.n_positive_integers(num_spatial_dims,
2384 strides=utils.n_positive_integers(num_spatial_dims, stride),

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