/external/tensorflow/tensorflow/core/kernels/image/ |
D | crop_and_resize_op_gpu.cu.cc | 80 const float in_x = (crop_width > 1) in CropAndResizeKernel() local 83 if (in_x < 0 || in_x > image_width - 1) { in CropAndResizeKernel() 93 const int left_x_index = floorf(in_x); in CropAndResizeKernel() 94 const int right_x_index = ceilf(in_x); in CropAndResizeKernel() 95 const float x_lerp = in_x - left_x_index; in CropAndResizeKernel() 121 const int closest_x_index = roundf(in_x); in CropAndResizeKernel() 172 const float in_x = (crop_width > 1) in CropAndResizeBackpropImageKernel() local 175 if (in_x < 0 || in_x > image_width - 1) { in CropAndResizeBackpropImageKernel() 184 const int left_x_index = floorf(in_x); in CropAndResizeBackpropImageKernel() 185 const int right_x_index = ceilf(in_x); in CropAndResizeBackpropImageKernel() [all …]
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D | resize_bilinear_op_gpu.cu.cc | 59 const float in_x = (static_cast<float>(x) + 0.5f) * width_scale - 0.5f; in ResizeBilinearKernel_faster() local 60 const int left_x_index = in_x > 0.0 ? floorf(in_x) : 0; in ResizeBilinearKernel_faster() 62 (in_x < in_width - 1) ? ceilf(in_x) : in_width - 1; in ResizeBilinearKernel_faster() 63 const float x_lerp = in_x - left_x_index; in ResizeBilinearKernel_faster() 138 const float in_x = (static_cast<float>(x) + 0.5f) * width_scale - 0.5f; in ResizeBilinearKernel() local 139 const int left_x_index = in_x > 0.0 ? floorf(in_x) : 0; in ResizeBilinearKernel() 141 (in_x < in_width - 1) ? ceilf(in_x) : in_width - 1; in ResizeBilinearKernel() 142 const float x_lerp = in_x - left_x_index; in ResizeBilinearKernel() 263 int in_x = in_x_start; in ResizeBilinearDeterministicGradKernel() local 264 while (out_x < out_x_center + 1 && in_x < resized_width) { in ResizeBilinearDeterministicGradKernel() [all …]
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D | crop_and_resize_op.cc | 275 const float in_x = (crop_width > 1) in operator ()() local 278 if (in_x < 0 || in_x > image_width - 1) { in operator ()() 284 const int left_x_index = floorf(in_x); in operator ()() 285 const int right_x_index = ceilf(in_x); in operator ()() 286 const float x_lerp = in_x - left_x_index; in operator ()() 305 const float in_x = (crop_width > 1) in operator ()() local 308 if (in_x < 0 || in_x > image_width - 1) { in operator ()() 314 const int closest_x_index = roundf(in_x); in operator ()() 495 const float in_x = (crop_width > 1) in operator ()() local 498 if (in_x < 0 || in_x > image_width - 1) { in operator ()() [all …]
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D | resize_nearest_neighbor_op_gpu.cu.cc | 55 const int in_x = in ResizeNearestNeighborNHWC() local 60 const int idx = (in_y * in_width + in_x) * channels + c; in ResizeNearestNeighborNHWC() 85 const int in_x = in LegacyResizeNearestNeighborNHWC() local 89 const int idx = (in_y * in_width + in_x) * channels + c; in LegacyResizeNearestNeighborNHWC() 104 int in_x = n % in_width; in ResizeNearestNeighborBackwardNHWC() local 117 floorf((static_cast<float>(in_x) + 0.5f) * width_scale)), in ResizeNearestNeighborBackwardNHWC() 135 int in_x = n % in_width; in LegacyResizeNearestNeighborBackwardNHWC() local 146 min((align_corners) ? static_cast<int>(roundf(in_x * width_scale)) in LegacyResizeNearestNeighborBackwardNHWC() 147 : static_cast<int>(floorf(in_x * width_scale)), in LegacyResizeNearestNeighborBackwardNHWC()
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D | resize_area_op.cc | 165 const float in_x = x * st.width_scale; in Compute() local 169 int64 v = std::floor(in_x); in Compute() 173 v < in_x ? (v + 1 > in_x1 ? st.width_scale : v + 1 - in_x) in Compute() 180 v < in_x ? (v + 1 > in_x1 ? st.width_scale : v + 1 - in_x) in Compute()
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D | resize_area_op_test.cc | 113 const float in_x = x * width_scale; in ResizeAreaBaseline() local 117 int64 x_start = std::floor(in_x); in ResizeAreaBaseline() 126 float scale_x = j < in_x in ResizeAreaBaseline() 127 ? (j + 1 > in_x1 ? width_scale : j + 1 - in_x) in ResizeAreaBaseline()
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/ |
D | transpose_conv.h | 69 for (int in_x = 0; in_x < input_width; ++in_x) { in TransposeConv() local 72 const int out_x_origin = (in_x * stride_width) - pad_width; in TransposeConv() 85 input_shape, batch, in_y, in_x, in_channel)]; in TransposeConv() 160 for (int in_x = 0; in_x < input_width; ++in_x) { in TransposeConv() local 163 const int out_x_origin = (in_x * stride_width) - pad_width; in TransposeConv() 176 input_shape, batch, in_y, in_x, in_channel)]; in TransposeConv()
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D | conv.h | 67 const int in_x = in_x_origin + dilation_width_factor * filter_x; in Conv() local 71 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in Conv() 80 in_x, in_channel)]; in Conv() 150 const int in_x = in_x_origin + dilation_width_factor * filter_x; in Conv() local 154 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in Conv() 163 in_x, in_channel)]; in Conv() 230 const int in_x = in_x_origin + dilation_width_factor * filter_x; in HybridConvPerChannel() local 235 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in HybridConvPerChannel() 238 input_shape, batch, in_y, in_x, in_channel)]; in HybridConvPerChannel()
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D | pooling.h | 62 const int in_x = in_x_origin + filter_x; in AveragePool() local 65 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in AveragePool() 118 const int in_x = in_x_origin + filter_x; in AveragePool() local 121 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in AveragePool() 171 const int in_x = in_x_origin + filter_x; in L2Pool() local 174 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in L2Pool() 224 const int in_x = in_x_origin + filter_x; in MaxPool() local 228 input_data[Offset(input_shape, batch, in_y, in_x, channel)]); in MaxPool() 278 const int in_x = in_x_origin + filter_x; in MaxPool() local 282 input_data[Offset(input_shape, batch, in_y, in_x, channel)]); in MaxPool()
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D | depthwiseconv_uint8.h | 140 const int in_x = in Run() local 146 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in Run() 149 input_data[Offset(input_shape, b, in_y, in_x, ic)]; in Run() 227 const int in_x = in RunPerChannel() local 233 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in RunPerChannel() 237 input_shape, batch, in_y, in_x, in_channel)]; in RunPerChannel()
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D | depthwiseconv_float.h | 67 const int in_x = in_x_origin + dilation_width_factor * filter_x; in DepthwiseConv() local 72 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in DepthwiseConv() 75 input_data[Offset(input_shape, b, in_y, in_x, ic)]; in DepthwiseConv()
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D | conv3d.h | 70 const int in_x = in Conv3D() local 75 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in Conv3D() 86 input_shape, batch, in_d, in_y, in_x, in_channel)]; in Conv3D()
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/external/tensorflow/tensorflow/core/kernels/linalg/ |
D | banded_triangular_solve_op.cc | 62 static void Run(const Tensor& in_x, const Tensor& in_y, bool lower, in Run() 68 int num_bands = in_x.dim_size(1); in Run() 69 int matrix_size = in_x.dim_size(2); in Run() 74 auto matrix = ConstTensorSliceToEigenMatrix(in_x, x_batch_index); in Run() 168 static void Launch(OpKernelContext* context, const Tensor& in_x, in Launch() 174 in_x.dim_size(1) * in_x.dim_size(2) * in_y.dim_size(2); in Launch() 183 auto matrix = ConstMatrixMap(in_x.flat<Scalar>().data(), in_x.dim_size(1), in Launch() 184 in_x.dim_size(2)); in Launch() 189 min_abs_pivot = matrix.row(in_x.dim_size(1) - 1).cwiseAbs().minCoeff(); in Launch() 196 [&in_x, &in_y, adjoint, lower, &bcast, out](int64 start, in Launch() [all …]
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D | matrix_triangular_solve_op_impl.h | 84 static void Run(const Tensor& in_x, const Tensor& in_y, bool lower, in Run() 93 auto matrix = ConstTensorSliceToEigenMatrix(in_x, x_batch_index); in Run() 120 static void Launch(OpKernelContext* context, const Tensor& in_x, 126 in_x.dim_size(1) * in_x.dim_size(1) * in_y.dim_size(2) / 2; 134 auto matrix = ConstMatrixMap(in_x.flat<Scalar>().data(), in_x.dim_size(1), 135 in_x.dim_size(2)); 142 [&in_x, &in_y, adjoint, lower, &bcast, out](int start, int limit) { 144 in_x, in_y, lower, adjoint, bcast, out, start, limit); 257 static void Launch(OpKernelContext* context, const Tensor& in_x, 262 const uint64 m = in_x.dim_size(1); [all …]
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/integer_ops/ |
D | depthwise_conv.h | 72 const int in_x = in_x_origin + dilation_width_factor * filter_x; in DepthwiseConvPerChannel() local 77 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in DepthwiseConvPerChannel() 81 input_shape, batch, in_y, in_x, in_channel)]; in DepthwiseConvPerChannel() 169 const int in_x = in_x_origin + dilation_width_factor * filter_x; in DepthwiseConvPerChannel() local 174 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in DepthwiseConvPerChannel() 178 input_shape, batch, in_y, in_x, in_channel)]; in DepthwiseConvPerChannel() 253 const int in_x = in_x_origin + dilation_width_factor * filter_x; in DepthwiseConvHybridPerChannel() local 258 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in DepthwiseConvHybridPerChannel() 262 input_shape, batch, in_y, in_x, in_channel)]; in DepthwiseConvHybridPerChannel()
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D | transpose_conv.h | 68 for (int in_x = 0; in_x < input_width; ++in_x) { in TransposeConv() local 71 const int out_x_origin = (in_x * stride_width) - pad_width; in TransposeConv() 84 input_shape, batch, in_y, in_x, in_channel)]; in TransposeConv() 165 for (int in_x = 0; in_x < input_width; ++in_x) { in TransposeConv() local 168 const int out_x_origin = (in_x * stride_width) - pad_width; in TransposeConv() 181 input_shape, batch, in_y, in_x, in_channel)]; in TransposeConv()
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D | conv.h | 74 const int in_x = in_x_origin + dilation_width_factor * filter_x; in ConvPerChannel() local 78 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in ConvPerChannel() 87 in_x, in_channel)]; in ConvPerChannel() 177 const int in_x = in_x_origin + dilation_width_factor * filter_x; in ConvPerChannel() local 181 (in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in ConvPerChannel() 190 in_x, in_channel)]; in ConvPerChannel()
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D | pooling.h | 62 const int in_x = in_x_origin + filter_x; in AveragePool() local 65 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in AveragePool() 122 const int in_x = in_x_origin + filter_x; in MaxPool() local 126 input_data[Offset(input_shape, batch, in_y, in_x, channel)]); in MaxPool() 178 const int in_x = in_x_origin + filter_x; in AveragePool() local 181 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in AveragePool() 238 const int in_x = in_x_origin + filter_x; in MaxPool() local 242 input_data[Offset(input_shape, batch, in_y, in_x, channel)]); in MaxPool()
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/external/tensorflow/tensorflow/core/kernels/ |
D | matmul_op_impl.h | 77 static void Run(const OpKernelContext* context, const Tensor& in_x, in Run() 82 auto Tx = in_x.tensor<Scalar, 3>(); in Run() 122 static void Run(const OpKernelContext* context, const Tensor& in_x, 131 auto Tx = in_x.flat_inner_dims<Scalar, 2>(); 136 auto Tx = in_x.tensor<Scalar, 3>(); 178 static void Run(const Tensor& in_x, const Tensor& in_y, bool adj_x, 187 auto x = ConstTensorSliceToEigenMatrix(in_x, x_batch_index); 228 static void Launch(OpKernelContext* context, const Tensor& in_x, 238 in_x.dim_size(1) * in_x.dim_size(2) * out->dim_size(2); 240 std::min(in_x.dim_size(1), in_x.dim_size(2)), out->dim_size(2)); [all …]
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D | conv_ops_fused_image_transform.cc | 237 float in_x = (cache_x - left_padding); in CalculatePerCachePixelParameters() local 238 if (in_x < 0) { in CalculatePerCachePixelParameters() 239 in_x = -(in_x + 1.0f - pad_offset); in CalculatePerCachePixelParameters() 240 } else if (in_x >= resized_width) { in CalculatePerCachePixelParameters() 241 in_x = (resized_width * 2.0f) - (in_x + 1.0f + pad_offset); in CalculatePerCachePixelParameters() 244 in_x *= st.width_scale; in CalculatePerCachePixelParameters() 246 result.left_x_index = static_cast<int64>(std::floor(in_x)); in CalculatePerCachePixelParameters() 248 std::min(static_cast<int64>(std::ceil(in_x)), (st.in_width - 1)); in CalculatePerCachePixelParameters() 250 result.x_lerp = static_cast<T1>(in_x - result.left_x_index); in CalculatePerCachePixelParameters()
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/external/tensorflow/tensorflow/lite/kernels/perception/ |
D | dense_image_warp.cc | 50 for (int in_x = 0; in_x < width; ++in_x) { in DenseImageWarp() local 52 in_y - flow_data[Offset(flow_shape, batch, in_y, in_x, 0)]; in DenseImageWarp() 54 in_x - flow_data[Offset(flow_shape, batch, in_y, in_x, 1)]; in DenseImageWarp() 81 output_data[Offset(input_shape, batch, in_y, in_x, c)] = interp; in DenseImageWarp()
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D | max_unpooling_2d.cc | 43 for (int in_x = 0; in_x < input_shape.Dims(2); ++in_x) { in MaxUnpooling() local 46 Offset(input_shape, batch, in_y, in_x, channel); in MaxUnpooling()
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/external/deqp/external/openglcts/modules/glesext/tessellation_shader/ |
D | esextcTessellationShaderUtils.hpp | 52 _ivec4(int in_x, int in_y, int in_z, int in_w) in _ivec4() 54 x = in_x; in _ivec4() 92 _vec2(float in_x, float in_y) in _vec2() 94 x = in_x; in _vec2() 134 _vec4(float in_x, float in_y, float in_z, float in_w) in _vec4() 136 x = in_x; in _vec4()
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/external/rust/crates/ring/crypto/fipsmodule/ec/asm/ |
D | ecp_nistz256-x86.pl | 769 { my ($S,$M,$Zsqr,$in_x,$tmp0)=map(32*$_,(0..4)); 788 &mov (&DWP($in_x+0,"esp"),"eax"); 789 &mov (&DWP($in_x+4,"esp"),"ebx"); 790 &mov (&DWP($in_x+8,"esp"),"ecx"); 791 &mov (&DWP($in_x+12,"esp"),"edx"); 796 &mov (&DWP($in_x+16,"esp"),"eax"); 797 &mov (&DWP($in_x+20,"esp"),"ebx"); 798 &mov (&DWP($in_x+24,"esp"),"ecx"); 799 &mov (&DWP($in_x+28,"esp"),"edx"); 827 &lea ("esi",&DWP($in_x,"esp")); [all …]
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/external/eigen/unsupported/test/ |
D | cxx11_tensor_cuda.cu | 718 Tensor<Scalar, 1> in_x(6); in test_cuda_zeta() local 724 in_x(0) = Scalar(1); in test_cuda_zeta() 725 in_x(1) = Scalar(1.5); in test_cuda_zeta() 726 in_x(2) = Scalar(4); in test_cuda_zeta() 727 in_x(3) = Scalar(-10.5); in test_cuda_zeta() 728 in_x(4) = Scalar(10000.5); in test_cuda_zeta() 729 in_x(5) = Scalar(3); in test_cuda_zeta() 745 std::size_t bytes = in_x.size() * sizeof(Scalar); in test_cuda_zeta() 754 cudaMemcpy(d_in_x, in_x.data(), bytes, cudaMemcpyHostToDevice); in test_cuda_zeta() 786 Tensor<Scalar, 1> in_x(7); in test_cuda_polygamma() local [all …]
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