/external/tensorflow/tensorflow/core/util/ |
H A D | tensor_format_test.cc | 105 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 [all...] |
H A D | tensor_format.h | 107 // 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.
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | depthtospace_op.cc | 57 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); [all...] |
H A D | spacetodepth_op.cc | 57 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; [all...] |
H A D | image_resize_ops.cc | 79 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 [all...] |
H A D | extract_image_patches_op.cc | 42 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); [all...] |
H A D | pooling_ops.cc | 38 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 [all...] |
H A D | conv_ops.cc | 177 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 [all...] |
/external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
H A D | ir_emission_utils.cc | 55 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) {
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H A D | conv_canonicalization.cc | 44 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) {
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H A D | ir_emitter.cc | 1002 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 [all...] |
/external/tensorflow/tensorflow/contrib/fused_conv/ops/ |
H A D | fused_conv2d_bias_activation_op.cc | 63 constexpr int num_spatial_dims = 2; 65 GetTensorDimsFromSpatialDims(num_spatial_dims, data_format); 71 GetFilterDimIndex<num_spatial_dims>(filter_format, 'O'));
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/external/tensorflow/tensorflow/python/ops/ |
H A D | nn_ops.py | 225 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] [all...] |
/external/tensorflow/tensorflow/core/kernels/ |
H A D | conv_grad_ops.cc | 98 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
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H A D | conv_grad_ops.h | 242 Status ConvBackpropComputeDimensions(StringPiece label, int num_spatial_dims, 253 StringPiece label, int num_spatial_dims, const TensorShape& input_shape,
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/external/tensorflow/tensorflow/core/framework/ |
H A D | common_shape_fns.cc | 391 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 [all...] |
/external/tensorflow/tensorflow/python/kernel_tests/ |
H A D | atrous_convolution_test.py | 52 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
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/external/tensorflow/tensorflow/compiler/xla/service/ |
H A D | shape_inference.cc | 1611 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; [all...] |
H A D | hlo_evaluator.cc | 903 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);
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/external/tensorflow/tensorflow/core/ops/ |
H A D | array_ops.cc | 2178 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 [all...] |
/external/tensorflow/tensorflow/compiler/xla/client/ |
H A D | computation_builder.cc | 594 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) {
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H A D | computation_builder.h | 366 int num_spatial_dims = 2);
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/external/tensorflow/tensorflow/compiler/xla/python/ |
H A D | xla_client.py | 1070 def _GetConvDimensionNumbers(self, num_spatial_dims): 1072 nd = num_spatial_dims
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/external/tensorflow/tensorflow/compiler/tests/ |
H A D | randomized_tests.cc | 311 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
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
H A D | layers.py | 2375 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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