/external/tensorflow/tensorflow/core/kernels/ |
H A D | conv_grad_ops.h | 37 // where both "X" and "Y" are in_depth x out_depth 45 // where each "a", "b", etc is batch x out_depth 236 int64 in_depth, out_depth; member in struct:tensorflow::ConvBackpropDimensions
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H A D | deep_conv2d.h | 26 // in_depth * out_depth product) convolutions (see deep_conv2d.cc for details). 81 int out_depth; member in struct:tensorflow::Conv2DArgs 94 out_depth(0) {} 101 int filter_cols, int in_depth, int out_depth,
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H A D | eigen_cuboid_convolution.h | 121 TensorIndex out_depth; local 126 out_depth = Eigen::divup(inputPlanes - kernelDepth + 1, 134 out_depth = 141 out_depth = 0; 164 pre_contract_dims[1] = out_depth * out_height * out_width; 171 pre_contract_dims[0] = out_depth * out_height * out_width; 190 post_contract_dims[1] = out_depth; 198 post_contract_dims[NumDims - 2] = out_depth;
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H A D | depthwise_conv_op.h | 41 int out_depth; member in struct:tensorflow::DepthwiseArgs 56 out_depth(0) {} 137 const int64 filter_inner_dim_size = args.out_depth; 211 const int64 output_scalar_size = args.out_depth % kPacketSize;
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H A D | eigen_spatial_convolutions_test.cc | 676 const int out_depth = in_depth; local 683 Tensor<float, 4> result(kern_filters, out_depth, out_height, out_width); 691 EXPECT_EQ(result.dimension(1), out_depth); 700 for (int i = 0; i < out_depth; ++i) { 737 const int out_depth = in_depth; local 744 Tensor<float, 4, RowMajor> result(out_width, out_height, out_depth, 753 EXPECT_EQ(result.dimension(2), out_depth); 762 for (int i = 0; i < out_depth; ++i) { 799 const int out_depth = 3; local 806 Tensor<float, 4> result(kern_filters, out_depth, out_heigh 851 const int out_depth = 3; local 905 const int out_depth = in_depth; local 971 const int out_depth = in_depth; local 1037 const int out_depth = 3; local 1092 const int out_depth = 3; local 1149 const int out_depth = ceil_div(in_depth, stride); local 1219 const int out_depth = ceil_div(in_depth, stride); local [all...] |
H A D | pooling_ops_common.h | 66 int out_depth; member in struct:tensorflow::PoolParameters
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H A D | conv_grad_ops_3d.cc | 77 const int64 out_depth = filter_shape.dim_size(4); \ 79 context, out_depth == GetTensorDim(out_backprop, data_format_, 'C'), \ 81 label, ": filter and out_backprop must have the same out_depth")); \ 191 padded_out_cols, out_depth}); 205 // out_depth for the filter and reverse the planes, rows and cols. 207 {filter_size[0], filter_size[1], filter_size[2], out_depth, in_depth}); 309 // [batch, out_z, out_y, out_x, out_depth] 311 // [out_depth, out_x, out_y, out_z, batch] 313 TensorShape padded_out_shape({out_depth, padded_out_planes, padded_out_rows, 346 // [out_depth, filter_siz 581 .set_output_feature_map_count(out_depth); variable 942 .set_output_feature_map_count(out_depth); variable [all...] |
H A D | conv_ops_3d.cc | 106 const int64 out_depth = filter.dim_size(4); variable 126 data_format_, in_batch, {{out[0], out[1], out[2]}}, out_depth); 184 const int64 out_depth = filter.dim_size(4); local 207 const uint64 n = out_depth; 234 const uint64 n = out_depth; 324 .set_feature_map_count(out_depth) 331 .set_output_feature_map_count(out_depth); 343 TensorShape({out_depth, in_depth, filter_planes, 357 {{out_planes, out_rows, out_cols}}, out_depth), 378 out_depth, [all...] |
H A D | depthwise_conv_op.cc | 88 const int64 out_depth = args.out_depth; local 90 const int64 output_scalar_size = out_depth % kPacketSize; 92 (out_depth / kPacketSize) * kPacketSize; 93 const int64 base_output_index = (out_r * args.out_cols + out_c) * out_depth; 166 const bool pad_filter = (args.out_depth % kPacketSize) == 0 ? false : true; 172 ((args.out_depth + kPacketSize - 1) / kPacketSize) * kPacketSize; 192 args.out_rows * args.out_cols * args.out_depth; 195 ((args.out_depth + kPacketSize - 1) / kPacketSize) * kPacketSize; 235 const int64 shard_cost = kCostMultiplier * args.out_cols * args.out_depth; 320 const int32 out_depth = in_depth * depth_multiplier; variable 366 << out_rows << ", " << out_cols << ", " << out_depth << "]"; variable [all...] |
H A D | fractional_avg_pool_op.cc | 247 const int64 out_depth = out_backprop.dim_size(3); variable 276 out_depth, 303 for (int64 d = 0; d < out_depth; ++d) {
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H A D | conv_ops_using_gemm.cc | 459 // [ filter_rows, filter_cols, in_depth, out_depth] 485 // The last dimension for filter is out_depth. 486 const int out_depth = static_cast<int>(filter.dim_size(3)); variable 528 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth); 531 // [ in_batch, out_rows, out_cols, out_depth ] 542 << ", out_depth = " << out_depth; variable 551 out_depth, stride_rows, stride_cols, padding_,
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H A D | mkl_conv_ops.h | 164 // TF filter is always in (rows, cols, in_depth, out_depth) order. 168 int out_depth = static_cast<int>(filter_shape.dim_size(3)); local 171 // OIHW = (out_depth, in_depth, rows, cols) 173 mkldnn_sizes[MklDnnDims::Dim_O] = out_depth; 239 int out_depth = filter_shape.dim_size(3); local 253 ShapeFromFormat(data_format_, out_batch, out_rows, out_cols, out_depth); 259 mkldnn_sizes[MklDnnDims::Dim_C] = out_depth;
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H A D | mkl_pooling_ops_common.h | 54 int out_depth; member in struct:tensorflow::MklPoolParameters 76 out_depth(0), 148 mkl_pool_params.out_depth,
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H A D | nn_ops_test.cc | 106 int out_depth, int filter_rows, int filter_cols, 137 num_ops = static_cast<int64>(batch * in_depth * out_depth) * 144 num_ops = static_cast<int64>(batch * in_depth * out_depth) * 151 SetConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, 153 SetConstOp("output_backprop", {batch, out_rows, out_cols, out_depth}, 160 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), 500 int out_depth, int filter_rows, 555 SetConstOp("output_backprop", {batch, out_rows, out_cols, out_depth}, 105 BM_ConvFloat(int iters, int batch, int rows, int cols, int in_depth, int out_depth, int filter_rows, int filter_cols, CONV_OP op, int num_threads, int stride, Padding padding, bool use_gpu, DataType data_type, const string& label) argument 498 BM_ConvFloatDepthwise(int iters, int batch, int rows, int cols, int in_depth, int depth_multiplier, int out_depth, int filter_rows, int filter_cols, DEPTHWISE_CONV_OP op, int num_threads, int stride, Padding padding, bool use_gpu, const string& label) argument
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H A D | conv_grad_filter_ops.cc | 133 auto out_depth = output.dimension(3); local 145 desc.K = out_depth; 410 const size_t size_B = output_image_size * dims.out_depth; 412 const size_t size_C = filter_total_size * dims.out_depth; 433 dims.spatial_dims[1].output_size * dims.out_depth; 447 TensorMap C(filter_backprop_data, filter_total_size, dims.out_depth); 485 dims.out_depth); 699 const uint64 n = dims.out_depth; 702 // [batch, out_rows, out_cols, out_depth] 714 // [1, 1, in_depth, out_depth] [all...] |
H A D | conv_grad_input_ops.cc | 139 auto out_depth = output_backward.dimension(3); local 150 desc.K = out_depth; 428 const size_t size_A = output_image_size * dims.out_depth; 430 const size_t size_B = filter_total_size * dims.out_depth; 474 dims.spatial_dims[1].output_size * dims.out_depth; 503 output_image_size, dims.out_depth); 504 ConstTensorMap B(filter_data, filter_total_size, dims.out_depth); 544 ConstMatrixMap A(out_data, output_image_size, dims.out_depth); 545 ConstMatrixMap B(filter_data, filter_total_size, dims.out_depth); 768 const uint64 k = dims.out_depth; [all...] |
H A D | conv_ops.cc | 139 int /*out_cols*/, int /*out_depth*/, int /*dilation_rows*/, 155 int out_cols, int out_depth, int dilation_rows, 161 in_depth, out_depth, out_rows, out_cols)) { 176 args.out_depth = out_depth; 196 int out_cols, int out_depth, int stride_rows, int stride_cols, 210 int out_cols, int out_depth, int dilation_rows, 221 desc.K = out_depth; 308 // [ filter_rows, filter_cols, in_depth, out_depth] 334 // The last dimension for filter is out_depth 151 Run(OpKernelContext* ctx, const Tensor& input, const Tensor& filter, int batch, int input_rows, int input_cols, int in_depth, int filter_rows, int filter_cols, int pad_rows, int pad_cols, int out_rows, int out_cols, int out_depth, int dilation_rows, int dilation_cols, int stride_rows, int stride_cols, Tensor* output, TensorFormat data_format) argument 192 Run(OpKernelContext* ctx, const Tensor& input, const Tensor& filter, int batch, int input_rows, int input_cols, int in_depth, int filter_rows, int filter_cols, int pad_rows, int pad_cols, int out_rows, int out_cols, int out_depth, int stride_rows, int stride_cols, int dilation_rows, int dilation_cols, Tensor* output, TensorFormat data_format) argument 206 Run(OpKernelContext* ctx, const Tensor& input, const Tensor& filter, int batch, int input_rows, int input_cols, int in_depth, int filter_rows, int filter_cols, int pad_rows, int pad_cols, int out_rows, int out_cols, int out_depth, int dilation_rows, int dilation_cols, int stride_rows, int stride_cols, Tensor* output, TensorFormat data_format) argument 335 const int out_depth = static_cast<int>(filter.dim_size(3)); variable 397 << ", out_depth = " << out_depth; variable [all...] |
H A D | conv_ops_fused.cc | 759 // [ filter_rows, filter_cols, in_depth, out_depth] 787 // The last dimension for filter is out_depth. 788 const int out_depth = static_cast<int>(filter.dim_size(3)); variable 832 ShapeFromFormat(FORMAT_NHWC, batch, out_rows, out_cols, out_depth); 837 // [ in_batch, out_rows, out_cols, out_depth ] 850 << ", out_depth = " << out_depth << ", DoResize=" << DoResize; 859 filter_cols, out_depth, stride_rows, stride_cols, padding_,
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H A D | depthwise_conv_grad_op.cc | 106 const int32 out_depth = static_cast<int32>(out_depth_raw); \ 108 context, (depth_multiplier * in_depth) == out_depth, \ 110 label, ": depth_multiplier * in_depth not equal to out_depth")); \ 142 args.out_depth = out_depth; \ 149 << ", " << out_depth << "]"; 162 // 'out_backprop': [batch, out_rows, out_cols, out_depth] 209 const int64 vectorized_size = (args.out_depth / kPacketSize) * kPacketSize; 210 const int64 scalar_size = args.out_depth % kPacketSize; 221 out_backprop + (out_r * args.out_cols + out_c) * args.out_depth; 283 const int64 out_depth = args.out_depth; local 653 const int64 out_depth = args.out_depth; local 800 const int64 out_depth = args.out_depth; local [all...] |
H A D | mkl_conv_ops.cc | 132 // The last dimension for filter is out_depth. 133 const int out_depth = static_cast<int>(filter.dim_size(3)); variable 182 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth); 185 // [ in_batch, out_rows, out_cols, out_depth ] 220 mkl_context.out_sizes[MklDims::C] = static_cast<size_t>(out_depth); 234 // TF filter dimension order (out_depth, in_depth, cols, rows) -> 235 // MKL filter dimension order (out_depth, in_depth, rows, cols) 239 mkl_context.filter_sizes[3] = filter.dim_size(3); // out_depth 241 // TF filter layout - (rows, cols, in_depth, out_depth) 247 mkl_context.filter_strides[3] = 1; // out_depth [all...] |
/external/tensorflow/tensorflow/core/grappler/costs/ |
H A D | utils_test.cc | 67 int out_depth = 5; local 77 CreateConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, 81 CreateConstOp("output_backprop", {batch, out_rows, out_cols, out_depth}, 92 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}),
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/external/tensorflow/tensorflow/core/kernels/neon/ |
H A D | neon_depthwise_conv_op.cc | 86 const int32 out_depth = in_depth * depth_multiplier; variable 97 TensorShape out_shape({batch, out_rows, out_cols, out_depth}); 105 // [ in_batch, out_rows, out_cols, out_depth ] 115 << out_rows << ", " << out_cols << ", " << out_depth << "]"; variable
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/external/tensorflow/tensorflow/contrib/hvx/hexagon_controller/src_impl/ |
H A D | graph_functions_wrapper.c | 216 uint32_t* out_width, uint32_t* out_depth, uint8_t* out_vals, 246 *out_depth = output.depth; 252 *out_width, *out_depth, *out_data_byte_size); 259 uint32_t out_batches, out_height, out_width, out_depth; local 268 &out_batches, &out_height, &out_width, &out_depth, 273 s_output_values, out_batches * out_height * out_width * out_depth, 276 out_width, out_depth, out_data_size); 279 out_batches * out_height * out_width * out_depth)); 212 hexagon_controller_ExecuteGraph( const uint32_t nn_id, const uint32_t batches, const uint32_t height, const uint32_t width, const uint32_t depth, uint8_t* int_data, const uint32_t int_data_size, uint32_t* out_batches, uint32_t* out_height, uint32_t* out_width, uint32_t* out_depth, uint8_t* out_vals, const uint32_t output_val_byte_size, uint32_t* out_data_byte_size) argument
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H A D | hexagon_controller.c | 187 const uint32_t out_depth = output0->depth; local 203 out_batches * out_height * out_width * out_depth, OUT_RANKING_SIZE, 206 out_height, out_width, out_depth, out_data_size, out_buf_byte_size);
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/external/mesa3d/src/mesa/state_tracker/ |
H A D | st_cb_drawpixels.c | 124 struct ureg_dst out_color, out_depth, out_stencil; local 152 out_depth = ureg_DECL_output(ureg, TGSI_SEMANTIC_POSITION, 0); 172 ureg_TEX(ureg, ureg_writemask(out_depth, TGSI_WRITEMASK_Z),
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