/external/tensorflow/tensorflow/python/framework/ |
D | common_shapes.py | 205 in_cols = input_shape[2] 225 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows, 264 in_cols = input_shape[2] 286 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows, 329 in_cols = input_shape[2] 349 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows, 397 in_cols = input_shape[2] 412 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, ksize_r, 465 in_cols = input_shape[2] 484 out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, ksize_r, [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | pooling_ops_3d_sycl.h | 34 const int in_rows, const int in_cols, const int out_planes, in SYCL3DPoolParams() 43 in_cols_(in_cols), in SYCL3DPoolParams() 58 const int in_rows, const int in_cols, in SYCL3DPoolParams() 63 : SYCL3DPoolParams(depth, batch, in_planes, in_rows, in_cols, in SYCL3DPoolParams() 125 const int in_rows, const int in_cols, const int out_planes, in MaxPool3DSYCL() argument 132 : p_(depth, batch, in_planes, in_rows, in_cols, out_planes, out_rows, in MaxPool3DSYCL() 192 const int in_cols = GetTensorDim(tensor_in, data_format, '2'); 207 MaxPool3DSYCL<T> max_pool(depth, batch, in_planes, in_rows, in_cols, 236 const int in_rows, const int in_cols, 245 : p_(depth, batch, in_planes, in_rows, in_cols, output_shape, window, [all …]
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D | eigen_spatial_convolutions_test.cc | 671 const int in_cols = 7; in TEST() local 680 const int out_width = in_cols; in TEST() 682 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST() 712 r - off_r + j < in_rows && c - off_c + k < in_cols) { in TEST() 732 const int in_cols = 7; in TEST() local 741 const int out_width = in_cols; in TEST() 743 Tensor<float, 4, RowMajor> input(in_cols, in_rows, in_depth, in_channels); in TEST() 774 r - off_r + j < in_rows && c - off_c + k < in_cols) { in TEST() 794 const int in_cols = 5; in TEST() local 805 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST() [all …]
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D | depthwise_conv_op_gpu.h | 47 args.in_cols <= 32 && args.in_rows == args.out_rows && in CanLaunchDepthwiseConv2dGPUSmall() 48 args.in_cols == args.out_cols && args.pad_rows >= 0 && in CanLaunchDepthwiseConv2dGPUSmall() 52 (args.in_rows + 1) / 2 * args.in_cols; in CanLaunchDepthwiseConv2dGPUSmall() 60 args.in_cols <= 32 && args.in_rows == args.out_rows && in CanLaunchDepthwiseConv2dBackpropFilterGPUSmall() 61 args.in_cols == args.out_cols && args.pad_rows >= 0 && in CanLaunchDepthwiseConv2dBackpropFilterGPUSmall() 64 args.filter_rows * args.filter_cols <= args.in_cols * block_height; in CanLaunchDepthwiseConv2dBackpropFilterGPUSmall() 79 const int in_width = args.in_cols; in DepthwiseConv2dGPUKernelNHWC() 186 const int in_width = args.in_cols; in DepthwiseConv2dGPUKernelNHWCSmall() 196 assert(blockDim.y == args.in_cols); in DepthwiseConv2dGPUKernelNHWCSmall() 319 const int in_width = args.in_cols; in DepthwiseConv2dGPUKernelNCHW() [all …]
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D | conv_ops_3d.cc | 216 int64 in_cols = GetTensorDim(input, data_format, '2'); in launch() local 235 0, (out_cols - 1) * strides[2] + filter_cols - in_cols); in launch() 244 const uint64 m = in_batch * in_planes * in_rows * in_cols; in launch() 267 filter_cols == in_cols && padding == Padding::VALID && in launch() 272 const uint64 k = in_planes * in_rows * in_cols * in_depth; in launch() 306 const int64 new_in_cols = in_cols + cols_odd; in launch() 323 in_cols = new_in_cols; in launch() 330 FORMAT_NCHW, in_batch, {{in_planes, in_rows, in_cols}}, in_depth); in launch() 354 .set_spatial_dim(DimIndex::X, in_cols) in launch() 420 {{in_planes, in_rows, in_cols}}, in launch()
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D | avgpooling_op.cc | 265 const int64 in_cols = output_shape.dim_size(2); in Compute() local 291 GetWindowedOutputSize(in_cols, window_cols, col_stride, in Compute() 299 in_rows, in_cols, window_rows, window_cols, row_stride, in Compute() 320 GetBroadcastSize(c, in_cols, window_cols, col_stride, in Compute() 328 int64 input_index = (b * in_rows + r_dst) * in_cols + c_dst; in Compute() 348 window_rows * window_cols * depth_window * in_rows * in_rows * in_cols; in Compute() 506 const int64 in_cols = output_shape.dim_size(2); in Compute() local 531 GetWindowedOutputSize(in_cols, window_cols, col_stride, in Compute() 537 in_cols, // width in Compute()
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D | depthwise_conv_op.h | 29 int in_cols; member 46 in_cols(0), in DepthwiseArgs() 231 in_c < args.in_cols) { 232 auto* in = input + (in_r * args.in_cols + in_c) * args.in_depth;
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D | deep_conv2d.h | 71 int in_cols; member 86 in_cols(0), in Conv2DArgs()
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D | conv_ops.cc | 187 args.in_cols = input_cols; in Run() 600 int64 in_cols = GetTensorDim(input, data_format, 'W'); in operator ()() local 615 const uint64 m = in_batch * in_rows * in_cols; in operator ()() 637 } else if (patch_rows == in_rows && patch_cols == in_cols && in operator ()() 687 status = GetWindowedOutputSizeVerboseV2(in_cols, patch_cols, col_dilation, in operator ()() 709 const int64 new_in_cols = in_cols + padding_cols_diff; in operator ()() 738 in_cols = new_in_cols; in operator ()() 744 ShapeFromFormat(FORMAT_NCHW, in_batch, in_rows, in_cols, in_depths); in operator ()() 767 .set_width(in_cols) in operator ()() 832 in_cols}}, // in_cols in operator ()()
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D | fractional_avg_pool_op.cc | 255 const int64 in_cols = orig_input_tensor_shape_flat(2); in Compute() local 274 in_cols * in_rows * in_batch); in Compute() 281 const int64 in_max_col_index = in_cols - 1; in Compute() 301 const int64 in_index = (b * in_rows + in_r) * in_cols + in_c; in Compute()
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D | depthwise_conv_grad_op.cc | 135 args.in_cols = input_cols; \ 294 const int64 base_output_index = (in_r * args.in_cols + in_c) * in_depth; in ComputeBackpropInput() 410 args.in_rows * args.in_cols * args.in_depth; in operator ()() 436 for (int64 in_c = 0; in_c < args.in_cols; ++in_c) { in operator ()() 452 const int64 shard_cost = args.in_rows * args.in_cols * args.out_depth; in operator ()() 467 for (int in_c = 0; in_c < args.in_cols; ++in_c) { in DepthwiseConvBackpropInputReference() 507 args.in_depth * (in_c + args.in_cols * (in_r + args.in_rows * b)); in DepthwiseConvBackpropInputReference() 870 args.in_rows * args.in_cols * args.in_depth; in operator ()() 965 in_c < args.in_cols) { in DepthwiseConvBackpropFilterReference() 973 (in_c + args.in_cols * (in_r + args.in_rows * b)); in DepthwiseConvBackpropFilterReference()
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D | pooling_ops_common.h | 199 const int32 in_cols = params.tensor_in_cols; in SpatialMaxPool() local 220 for (int32 w = 0; w < in_cols; ++w) { in SpatialMaxPool() 234 const int32 in_offset = (b * in_rows + h) * in_cols + w; in SpatialMaxPool() 446 const int32 in_cols = params.tensor_in_cols; 467 for (int32 w = 0; w < in_cols; ++w) { 481 const int32 in_offset = (b * in_rows + h) * in_cols + w;
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D | extract_image_patches_op.cc | 71 const int in_cols = input.dim_size(2); in Compute() local 92 GetWindowedOutputSize(in_cols, ksize_cols_eff, stride_cols, in Compute()
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D | extract_volume_patches_op.cc | 78 const int in_cols = input.dim_size(3); in Compute() local 118 GetWindowedOutputSize(in_cols, ksize_cols, stride_cols, in Compute()
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D | conv_ops_fused_impl.h | 583 int64 in_cols = GetTensorDim(input, params.data_format, 'W'); 620 (patch_cols - 1) * dimensions.dilation_cols + 1 - in_cols); 626 int64 new_in_cols = in_cols + cols_odd; 642 in_cols = new_in_cols; 649 ShapeFromFormat(FORMAT_NCHW, in_batch, in_rows, in_cols, in_depths); 682 .set_width(in_cols) 756 in_cols}}, // in_cols
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D | maxpooling_op.cc | 105 const int32 in_cols = params.tensor_in_cols; in SpatialMaxPoolWithArgMaxHelper() local 129 for (int w = 0; w < in_cols; ++w) { in SpatialMaxPoolWithArgMaxHelper() 141 const int64 in_index = (b * in_rows + h) * in_cols + w; in SpatialMaxPoolWithArgMaxHelper() 158 out_arg_max_ref = (h * in_cols + w) * depth + d; in SpatialMaxPoolWithArgMaxHelper() 174 const int64 in_size = in_rows * in_cols * depth; in SpatialMaxPoolWithArgMaxHelper() 585 const int32 in_cols = params.tensor_in_cols; in SpatialMaxPoolGradGrad() local 612 const int w_end = std::min(w_start + window_cols, in_cols); in SpatialMaxPoolGradGrad() 622 const int in_index = (b * in_rows + h) * in_cols + w; in SpatialMaxPoolGradGrad()
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D | depthwise_conv_op.cc | 191 args.in_rows * args.in_cols * args.in_depth; in operator ()() 415 args.in_cols = input_cols; in Compute()
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D | pooling_ops_3d.cc | 581 const int32 in_cols = params.tensor_in_cols; in launch() local 616 const int w_end = std::min(w_start + window_cols, in_cols); in launch() 630 ((b * in_planes + p) * in_rows + h) * in_cols + w; in launch()
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D | deep_conv2d.cc | 652 if (in_c < 0 || in_c >= args.in_cols) continue; in operator ()() 654 auto* in = input + (in_r * args.in_cols + in_c) * args.in_depth; in operator ()() 1114 const int64 input_image_size = args.in_rows * args.in_cols * in_depth; in operator ()()
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/external/tensorflow/tensorflow/compiler/xla/tests/ |
D | pad_test.cc | 344 constexpr int64 in_cols = 35; in XLA_TEST_P() local 345 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 366 constexpr int64 in_cols = 129; in XLA_TEST_P() local 370 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 393 constexpr int64 in_cols = 129; in XLA_TEST_P() local 397 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 421 constexpr int64 in_cols = 11; in XLA_TEST_P() local 425 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P()
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_ExtractVolumePatches.pbtxt | 6 5-D Tensor with shape `[batch, in_planes, in_rows, in_cols, depth]`.
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D | api_def_ExtractImagePatches.pbtxt | 6 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.
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/external/tensorflow/tensorflow/core/ops/ |
D | array_ops.cc | 2483 auto in_cols = c->Value(in_cols_dim); in __anon7c94107b3902() local 2494 in_cols, ksize_cols_eff, stride_cols, padding, &output_cols, in __anon7c94107b3902() 2589 auto in_cols = c->Value(in_cols_dim); in __anon7c94107b3a02() local 2603 in_cols, ksize_cols, stride_cols, padding, &output_cols, in __anon7c94107b3a02()
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D | nn_ops.cc | 937 auto in_cols = c->Value(in_cols_dim); in __anon3e672dd81d02() local 952 in_cols, filter_cols_eff, stride_cols, padding, &output_cols, in __anon3e672dd81d02()
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/external/tensorflow/tensorflow/stream_executor/cuda/ |
D | cuda_dnn.cc | 2611 int64 in_cols = input_desc.ndims() == 1 ? 1 : input_desc.width(); in ShouldIncludeWinogradNonfusedAlgo() local 2615 std::max(in_depths, out_depths) * in_cols * in_rows * in ShouldIncludeWinogradNonfusedAlgo()
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