/external/tensorflow/tensorflow/core/kernels/ |
D | dilation_ops_gpu.cu.cc | 41 int depth, int filter_rows, int filter_cols, int output_rows, in DilationKernel() argument 58 for (int w = 0; w < filter_cols; ++w) { in DilationKernel() 64 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationKernel() 81 int filter_cols, int output_rows, int output_cols, int stride_rows, in DilationBackpropInputKernel() argument 103 for (int w = 0; w < filter_cols; ++w) { in DilationBackpropInputKernel() 109 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationBackpropInputKernel() 131 int filter_cols, int output_rows, int output_cols, int stride_rows, in DilationBackpropFilterKernel() argument 153 for (int w = 0; w < filter_cols; ++w) { in DilationBackpropFilterKernel() 159 filter_ptr[d + depth * (w + filter_cols * h)]; in DilationBackpropFilterKernel() 170 filter_backprop_ptr + d + depth * (w_max + filter_cols * h_max), in DilationBackpropFilterKernel() [all …]
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D | depthwise_conv_grad_op.cc | 88 const int64 filter_cols = filter_shape.dim_size(1); \ 132 input_cols, filter_cols, stride_, padding_, \ 150 args.filter_cols = filter_cols; \ 160 << "]; Filter: [" << filter_rows << ", " << filter_cols << ", " \ 201 const int64 filter_cols = args.filter_cols; in CopyOutputBackpropRegion() local 212 static_cast<int64>(0), (in_c - filter_cols + pad_cols + stride) / stride); in CopyOutputBackpropRegion() 216 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in CopyOutputBackpropRegion() 218 (out_c_end - out_c_start + 1) < args.filter_cols) { in CopyOutputBackpropRegion() 233 (f_r * filter_cols + f_c) * padded_filter_inner_dim_size; in CopyOutputBackpropRegion() 299 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in ComputeBackpropInput() [all …]
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D | deep_conv2d.h | 74 int filter_cols; member 89 filter_cols(0), in Conv2DArgs() 101 int filter_cols, int in_depth, int out_depth,
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D | depthwise_conv_op.cc | 95 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in Run() 176 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()() 199 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; in operator ()() 369 const int32 filter_cols = filter.dim_size(1); in Compute() local 386 input_cols, filter_cols, stride_, padding_, in Compute() 412 /*filter_cols=*/filter_cols, in Compute() 419 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute() 436 TensorShape{filter_rows, filter_cols, filter_in_depth, out_depth}; in Compute() 457 args.filter_cols = filter_cols; in Compute()
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D | depthwise_conv_op.h | 32 int filter_cols; member 49 filter_cols(0), in DepthwiseArgs() 145 const int64 filter_spatial_size = args.filter_rows * args.filter_cols; 221 for (int64 f_c = 0; f_c < args.filter_cols; ++f_c) { 232 if (f_c == args.filter_cols - 1) { 275 for (int64 f_c = 0; f_c < args.filter_cols; ++f_c) { 308 for (int64 f_c = 0; f_c < args.filter_cols; ++f_c) {
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D | dilation_ops.cc | 93 const int filter_cols = filter.dim_size(1); in ParseSizes() local 104 filter_cols + (filter_cols - 1) * (*rate_cols - 1); in ParseSizes() 174 const int filter_cols = filter.dimension(1); in operator ()() local 191 for (int w = 0; w < filter_cols; ++w) { in operator ()() 283 const int filter_cols = filter.dimension(1); in operator ()() local 308 for (int w = 0; w < filter_cols; ++w) { in operator ()() 403 const int filter_cols = filter.dimension(1); in operator ()() local 428 for (int w = 0; w < filter_cols; ++w) { in operator ()()
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D | depthwise_conv_op_gpu.h | 60 args.pad_cols < args.filter_cols && 61 args.filter_rows * args.filter_cols <= 73 args.pad_cols < args.filter_cols && block_height <= args.in_rows && 74 args.filter_rows * args.filter_cols <= args.in_cols * block_height; 97 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; 208 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; 344 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; 499 kKnownFilterWidth < 0 ? args.filter_cols : kKnownFilterWidth; 656 const int tile_width = args.in_cols + args.filter_cols - 1; 659 const int filter_pixels = args.filter_rows * args.filter_cols; [all …]
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D | conv_ops.cc | 224 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument 240 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument 246 !CanUseDeepConv2D(stride_rows, stride_cols, filter_rows, filter_cols, in Run() 257 args.filter_cols = filter_cols; in Run() 281 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument 295 int filter_cols, int pad_rows, int pad_cols, int out_rows, in Run() argument 309 desc.S = filter_cols; in Run() 450 const int filter_cols = static_cast<int>(filter.dim_size(1)); in ComputeConv2DDimension() local 481 input_cols, filter_cols, dilation_cols, stride_cols, params.padding, in ComputeConv2DDimension() 489 dimensions->filter_cols = filter_cols; in ComputeConv2DDimension() [all …]
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D | eigen_benchmark.h | 127 Eigen::Index filter_cols = filter_dims[1]; in SpatialConvolutionBackwardKernel() local 145 input, output_backward, filter_rows, filter_cols); in SpatialConvolutionBackwardKernel() 262 Eigen::Index filter_cols = filter_dims[1]; in CuboidConvolutionBackwardKernel() local 281 input, output_backward, filter_planes, filter_rows, filter_cols); in CuboidConvolutionBackwardKernel()
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D | conv_ops_using_gemm.cc | 508 const int filter_cols = static_cast<int>(filter.dim_size(1)); in Compute() local 527 GetWindowedOutputSize(input_cols, filter_cols, stride_cols, in Compute() 539 << ", filter_cols = " << filter_cols in Compute() 552 in_depth, filter.flat<T>().data(), filter_rows, filter_cols, in Compute()
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D | deep_conv2d.cc | 74 static int64 GetDirectConvCost(int filter_rows, int filter_cols, int in_depth, in GetDirectConvCost() argument 76 return filter_rows * filter_cols * in_depth * out_depth * out_rows * out_cols; in GetDirectConvCost() 98 int filter_cols, int in_depth, int out_depth, in CanUseDeepConv2D() argument 103 filter_cols != 3) { in CanUseDeepConv2D() 119 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D() 301 std::max(int64{0}, args.filter_cols - base_filter_cols); in operator ()() 338 if (f_c >= args.filter_cols) continue; in operator ()() 342 (args.in_depth * (f_r * args.filter_cols + f_c)) + in operator ()() 483 const int64 shard_cost = args.filter_rows * args.filter_cols * in_depth * in operator ()() 961 std::max(int64{0}, args.filter_cols - base_filter_rows); in operator ()()
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D | conv_ops_3d.cc | 230 const int64 filter_cols = filter.dim_size(2); in launch() local 245 0, (out_cols - 1) * strides[2] + filter_cols - in_cols); in launch() 252 filter_cols == 1 && dilations[0] == 1 && dilations[1] == 1 && in launch() 279 filter_rows == in_rows && filter_cols == in_cols && in launch() 412 filter_desc.set_spatial_dim(DimIndex::X, filter_cols) in launch() 487 {{filter_planes, filter_rows, filter_cols}}, in launch()
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D | nn_ops_test.cc | 108 int filter_rows, int filter_cols, CONV_OP op, in BM_ConvFloat() argument 131 TF_CHECK_OK(GetWindowedOutputSize(cols, filter_cols, stride, padding, in BM_ConvFloat() 140 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloat() 147 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloat() 153 SetConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in BM_ConvFloat() 162 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in BM_ConvFloat() 517 int filter_rows, int filter_cols, in BM_ConvFloatDepthwise() argument 540 TF_CHECK_OK(GetWindowedOutputSize(cols, filter_cols, stride, padding, in BM_ConvFloatDepthwise() 550 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise() 561 static_cast<int64>(filter_rows * filter_cols) * in BM_ConvFloatDepthwise() [all …]
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D | conv_ops.h | 88 int filter_cols;
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D | quantized_conv_ops.cc | 530 const int64 filter_cols = filter.dim_size(1); in Compute() local 545 GetWindowedOutputSize(input_cols, filter_cols, stride, in Compute() 563 filter_rows, filter_cols, out_depth, offset_filter, stride, in Compute()
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D | conv_ops_fused_image_transform.cc | 807 const int filter_cols = static_cast<int>(filter.dim_size(1)); in Compute() local 827 GetWindowedOutputSize(padded_cols, filter_cols, stride_cols, in Compute() 842 << ", filter_cols = " << filter_cols in Compute() 857 filter_cols, out_depth, stride_rows, stride_cols, padding_, in Compute()
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D | eigen_spatial_convolutions_test.cc | 1384 int filter_count, int filter_cols, int filter_rows, in PackRhsHelper() argument 1486 filter_rows, filter_cols, // in PackRhsHelper() 1506 numext::ceil((input_cols_eff - filter_cols + 1.f) / col_strides); in PackRhsHelper() 1512 reshape_dims[0] = input_depth * filter_rows * filter_cols; // patch size in PackRhsHelper() 1582 int filter_count, int filter_cols, int filter_rows, in PackLhsHelper() argument 1589 eigen_assert(block_cols <= input_depth * filter_rows * filter_cols); in PackLhsHelper() 1595 Dimensions filter_dims(filter_count, filter_rows, filter_cols, input_depth); in PackLhsHelper() 1651 reshape_dims[1] = input_depth * filter_rows * filter_cols; in PackLhsHelper() 1710 const Index max_col = filter_rows * filter_cols * input_depth; in PackLhsHelper() 1739 "filter: count=", filter_count, " dims=", filter_rows, "x", filter_cols, in PackLhsHelper()
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/external/tensorflow/tensorflow/lite/kernels/internal/optimized/integer_ops/ |
D | fully_connected.h | 56 const int filter_cols = filter_shape.Dims(filter_dim_count - 1); in FullyConnected() local 57 TFLITE_DCHECK_EQ(filter_shape.FlatSize(), filter_rows * filter_cols); in FullyConnected() 66 lhs_params.cols = filter_cols; in FullyConnected() 70 rhs_params.rows = filter_cols; in FullyConnected()
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D | conv.h | 86 const int filter_cols = FlatSizeSkipDim(filter_shape, 0); in ConvPerChannel() local 94 TFLITE_DCHECK_EQ(filter_cols, gemm_input_rows); in ConvPerChannel() 99 lhs_params.cols = filter_cols; in ConvPerChannel()
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/external/tensorflow/tensorflow/core/kernels/mkl/ |
D | mkl_conv_ops.h | 222 int filter_cols = in GetFilterSizeInMklOrder() local 239 mkldnn_sizes[MKL_GROUP_FILTER_DIM_W] = filter_cols; in GetFilterSizeInMklOrder() 247 mkldnn_sizes[MklDnnDims::Dim_W] = filter_cols; in GetFilterSizeInMklOrder() 262 int filter_cols = in GetFilterSizeInMklOrder() local 276 mkldnn_sizes[MklDnnDims3D::Dim3d_W] = filter_cols; in GetFilterSizeInMklOrder() 349 int filter_planes, filter_rows, filter_cols; variable 352 filter_cols = filter_shape.dim_size(TF_2DFILTER_DIM_W); 356 filter_cols = filter_shape.dim_size(TF_3DFILTER_DIM_W); 417 input_cols, filter_cols, dilation_cols, stride_cols, 430 input_cols, filter_cols, dilation_cols, stride_cols,
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/external/tensorflow/tensorflow/core/util/ |
D | use_cudnn.cc | 74 const int32 filter_cols, const int32 in_depth, in IsCudnnSupportedFilterSize() argument 76 return in_depth == out_depth && filter_rows == filter_cols && in IsCudnnSupportedFilterSize()
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D | use_cudnn.h | 36 const int32 filter_cols, const int32 in_depth,
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | conv_ops_test.py | 859 filter_cols=3, 881 filter_cols=3, 1855 filter_cols, argument 1868 filter_shape = [filter_rows, filter_cols, in_depth // num_groups, out_depth] 1872 output_cols = (input_cols - filter_cols + stride_cols) // stride_cols 1880 output_cols = (input_cols + padding[2][0] + padding[2][1] - filter_cols + 1949 filter_cols=3, 1967 filter_cols=2, 1985 filter_cols=3, 2003 filter_cols=2, [all …]
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/external/tensorflow/tensorflow/core/kernels/neon/ |
D | neon_depthwise_conv_op.cc | 83 const int32 filter_cols = filter.dim_size(1); in Compute() local 95 GetWindowedOutputSize(input_cols, filter_cols, stride, in Compute() 112 << filter_cols << ", " << in_depth << ", " << depth_multiplier in Compute()
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/external/tensorflow/tensorflow/core/grappler/costs/ |
D | utils_test.cc | 69 int filter_cols = 3; in TEST() local 83 CreateConstOp("filter", {filter_rows, filter_cols, in_depth, out_depth}, in TEST() 98 std::vector<int32>({filter_rows, filter_cols, in_depth, out_depth}), in TEST()
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