/external/tensorflow/tensorflow/core/kernels/ |
D | eigen_spatial_convolutions_test.cc | 670 const int in_rows = 8; in TEST() local 679 const int out_height = in_rows; 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() 731 const int in_rows = 8; in TEST() local 740 const int out_height = in_rows; 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() 793 const int in_rows = 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 | avgpooling_op.cc | 298 const int64 in_rows = output_shape.dim_size(1); in Compute() local 325 GetWindowedOutputSize(in_rows, window_rows, row_stride, in Compute() 336 in_rows, in_cols, window_rows, window_cols, row_stride, in Compute() 347 GetBroadcastSize(r, in_rows, window_rows, row_stride, in Compute() 365 int64 input_index = (b * in_rows + r_dst) * in_cols + c_dst; in Compute() 385 window_rows * window_cols * depth_window * in_rows * in_rows * in_cols; in Compute() 562 const int64 in_rows = output_shape.dim_size(1); in Compute() local 585 GetWindowedOutputSize(in_rows, window_rows, row_stride, in Compute() 593 in_rows, // height in Compute()
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D | depthwise_conv_op.h | 28 int in_rows; member 45 in_rows(0), in DepthwiseArgs() 224 if (in_r >= 0 && in_r < args.in_rows && in_c >= 0 && 278 if (in_r >= 0 && in_r < args.in_rows && in_c >= 0 && 311 if (in_r >= 0 && in_r < args.in_rows && in_c >= 0 &&
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D | deep_conv2d.h | 70 int in_rows; member 85 in_rows(0), in Conv2DArgs()
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D | conv_ops_3d.cc | 224 int64 in_rows = GetTensorDim(input, data_format, '1'); in launch() local 243 0, (out_rows - 1) * strides[1] + filter_rows - in_rows); in launch() 256 const uint64 m = in_batch * in_planes * in_rows * in_cols; in launch() 279 filter_rows == in_rows && filter_cols == in_cols && in launch() 284 const uint64 k = in_planes * in_rows * in_cols * in_depth; in launch() 317 const int64 new_in_rows = in_rows + rows_odd; in launch() 334 in_rows = new_in_rows; in launch() 358 FORMAT_NCHW, in_batch, {{in_planes, in_rows, in_cols}}, in_depth); in launch() 401 .set_spatial_dim(DimIndex::Y, in_rows) in launch() 484 {{in_planes, in_rows, in_cols}}, in launch()
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D | depthwise_conv_op_gpu.h | 56 return args.depth_multiplier == 1 && args.stride == 1 && args.in_rows <= 32 && 57 args.in_cols <= 32 && args.in_rows == args.out_rows && 62 (args.in_rows + 1) / 2 * args.in_cols; 69 return args.depth_multiplier == 1 && args.stride == 1 && args.in_rows <= 32 && 70 args.in_cols <= 32 && args.in_rows == args.out_rows && 73 args.pad_cols < args.filter_cols && block_height <= args.in_rows && 91 const int in_height = args.in_rows; 202 const int in_height = args.in_rows; 338 const int in_height = args.in_rows; 493 const int in_height = args.in_rows; [all …]
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D | fractional_avg_pool_op.cc | 254 const int64 in_rows = orig_input_tensor_shape_flat(1); in Compute() local 274 in_cols * in_rows * in_batch); in Compute() 280 const int64 in_max_row_index = in_rows - 1; in Compute() 301 const int64 in_index = (b * in_rows + in_r) * in_cols + in_c; in Compute()
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D | fused_batch_norm_op.cc | 123 const int64 in_rows = GetTensorDim(x_input, tensor_format, 'H'); in operator ()() local 129 in_rows, in_cols, in_depths), in operator ()() 134 in_rows, in_cols, in_depths), in operator ()() 261 const int64 in_rows = GetTensorDim(x_input, tensor_format, 'H'); in operator ()() local 267 in_rows, in_cols, in_depths), in operator ()() 272 in_rows, in_cols, in_depths), in operator ()() 353 const int64 in_rows = GetTensorDim(x_input, tensor_format, 'H'); in operator ()() local 359 in_rows, in_cols, in_depths), in operator ()() 364 in_rows, in_cols, in_depths), in operator ()() 369 in_rows, in_cols, in_depths), in operator ()() [all …]
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D | pooling_ops_common.h | 236 const int32 in_rows = params.tensor_in_rows; in SpatialMaxPool() local 257 for (int32 h = 0; h < in_rows; ++h) { in SpatialMaxPool() 272 const int32 in_offset = (b * in_rows + h) * in_cols + w; in SpatialMaxPool() 497 const int32 in_rows = params.tensor_in_rows; 518 for (int32 h = 0; h < in_rows; ++h) { 533 const int32 in_offset = (b * in_rows + h) * in_cols + w;
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D | conv_ops.cc | 253 args.in_rows = input_rows; in Run() 667 int64 in_rows = GetTensorDim(input, data_format, 'H'); in operator ()() local 683 const uint64 m = in_batch * in_rows * in_cols; in operator ()() 705 } else if (patch_rows == in_rows && patch_cols == in_cols && in operator ()() 772 in_rows, patch_rows, row_dilation, row_stride, padding, &out_rows_check, in operator ()() 804 const int64 new_in_rows = in_rows + padding_rows_diff; in operator ()() 833 in_rows = new_in_rows; in operator ()() 841 ShapeFromFormat(FORMAT_NCHW, in_batch, in_rows, in_cols, in_depths); in operator ()() 882 .set_height(in_rows) in operator ()() 969 {{in_rows, // in_rows in operator ()()
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D | depthwise_conv_grad_op.cc | 146 args.in_rows = input_rows; \ 422 args.in_rows * args.in_cols * args.in_depth; in operator ()() 447 for (int64 in_r = 0; in_r < args.in_rows; ++in_r) { in operator ()() 464 const int64 shard_cost = args.in_rows * args.in_cols * args.out_depth; in operator ()() 478 for (int in_r = 0; in_r < args.in_rows; ++in_r) { in DepthwiseConvBackpropInputReference() 519 args.in_depth * (in_c + args.in_cols * (in_r + args.in_rows * b)); in DepthwiseConvBackpropInputReference() 911 args.in_rows * args.in_cols * args.in_depth; in operator ()() 1005 if (in_r >= 0 && in_r < args.in_rows && in_c >= 0 && in DepthwiseConvBackpropFilterReference() 1014 (in_c + args.in_cols * (in_r + args.in_rows * b)); in DepthwiseConvBackpropFilterReference()
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D | conv_ops_fused_impl.h | 461 int64 in_rows = GetTensorDim(input, params.data_format, 'H'); 503 const int64 new_in_rows = in_rows + padding_rows_diff; 536 in_rows = new_in_rows; 543 ShapeFromFormat(FORMAT_NCHW, in_batch, in_rows, in_cols, in_depths); 575 .set_height(in_rows) 648 {{in_rows, // in_rows
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D | maxpooling_op.cc | 112 const int32 in_rows = params.tensor_in_rows; in SpatialMaxPoolWithArgMaxHelper() local 136 for (int h = 0; h < in_rows; ++h) { in SpatialMaxPoolWithArgMaxHelper() 149 const int64 in_index = (b * in_rows + h) * in_cols + w; in SpatialMaxPoolWithArgMaxHelper() 183 const int64 in_size = in_rows * in_cols * depth; in SpatialMaxPoolWithArgMaxHelper() 592 const int32 in_rows = params.tensor_in_rows; in SpatialMaxPoolGradGrad() local 618 const int h_end = std::min(h_start + window_rows, in_rows); in SpatialMaxPoolGradGrad() 630 const int in_index = (b * in_rows + h) * in_cols + w; in SpatialMaxPoolGradGrad()
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D | depthwise_conv_op.cc | 196 args.in_rows * args.in_cols * args.in_depth; in operator ()() 453 args.in_rows = input_rows; in Compute()
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D | pooling_ops_3d.cc | 576 const int32 in_rows = params.tensor_in_rows; in launch() local 610 const int h_end = std::min(h_start + window_rows, in_rows); in launch() 626 ((b * in_planes + p) * in_rows + h) * in_cols + w; in launch()
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D | deep_conv2d.cc | 648 if (in_r < 0 || in_r >= args.in_rows) continue; 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 | 343 constexpr int64 in_rows = 35; in XLA_TEST_P() local 345 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 365 constexpr int64 in_rows = 129; in XLA_TEST_P() local 370 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 392 constexpr int64 in_rows = 129; in XLA_TEST_P() local 397 auto operand = absl::make_unique<Array2D<float>>(in_rows, in_cols); in XLA_TEST_P() 420 constexpr int64 in_rows = 8; 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/kernels/image/ |
D | extract_volume_patches_op.cc | 80 const int in_rows = input.dim_size(2); in Compute() local 118 GetWindowedOutputSize(in_rows, ksize_rows, stride_rows, in Compute()
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D | extract_image_patches_op.cc | 73 const int in_rows = input.dim_size(1); in Compute() local 92 GetWindowedOutputSize(in_rows, ksize_rows_eff, stride_rows, in Compute()
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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 | 2641 auto in_rows = c->Value(in_rows_dim); in __anon42d741193902() local 2650 in_rows, ksize_rows_eff, stride_rows, padding, &output_rows, in __anon42d741193902() 2747 auto in_rows = c->Value(in_rows_dim); in __anon42d741193a02() local 2759 in_rows, ksize_rows, stride_rows, padding, &output_rows, in __anon42d741193a02()
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D | nn_ops.cc | 1030 auto in_rows = c->Value(in_rows_dim); in __anonad10f3361702() local 1043 in_rows, filter_rows_eff, stride_rows, padding, &output_rows, in __anonad10f3361702()
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/external/tensorflow/tensorflow/compiler/mlir/tensorflow/ir/ |
D | tf_generated_ops.td | 4116 …nt16, TF_Uint32, TF_Uint64, TF_Uint8]>, [{4-D Tensor with shape `[batch, in_rows, in_cols, depth]`…
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