From b9070a42a44ec1a0102e2f0b04523d2e96392903 Mon Sep 17 00:00:00 2001 From: Matthew Jackson Date: Thu, 22 Aug 2019 16:13:27 +0100 Subject: COMPMID-2605: Add asymmetric padding support for Deconvolution layer Change-Id: I63b773bdce25f1342ccd3a08ded623a1508f70fe Signed-off-by: Matthew Jackson Reviewed-on: https://review.mlplatform.org/c/1797 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Reviewed-by: Giuseppe Rossini --- .../kernels/CLDeconvolutionLayerUpsampleKernel.cpp | 9 ++- .../kernels/CLDeconvolutionReshapeOutputKernel.cpp | 17 ++--- src/core/CPP/kernels/CPPUpsampleKernel.cpp | 8 +-- src/core/Utils.cpp | 21 ++++--- src/graph/nodes/DeconvolutionLayerNode.cpp | 5 +- .../CL/functions/CLDirectDeconvolutionLayer.cpp | 44 ++++++++----- .../CL/functions/CLGEMMDeconvolutionLayer.cpp | 4 +- .../NEON/functions/NEDeconvolutionLayer.cpp | 72 +++++++++++++++------- 8 files changed, 111 insertions(+), 69 deletions(-) (limited to 'src') diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp index 50f654680c..4ae9cabd1f 100644 --- a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp +++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp @@ -56,7 +56,6 @@ Status CLDeconvolutionLayerUpsampleKernel::validate(const ITensorInfo *input, co ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(idx_w) == 0); ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(idx_h) == 0); - ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric()); ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_c) != output->dimension(idx_c)); for(size_t i = 3; i < Coordinates::num_max_dimensions; ++i) @@ -104,12 +103,12 @@ void CLDeconvolutionLayerUpsampleKernel::run(const Window &window, cl::CommandQu const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const int out_start_x = _info.pad().first; - const int out_end_x = _output->info()->dimension(idx_w) - _info.pad().first + _info.stride().first - 1; + const int out_start_x = _info.pad_left(); + const int out_end_x = _output->info()->dimension(idx_w) - _info.pad_right() + _info.stride().first - 1; const int out_step_x = _info.stride().first; - const int out_start_y = _info.pad().second; - const int out_end_y = _output->info()->dimension(idx_h) - _info.pad().second + _info.stride().second - 1; + const int out_start_y = _info.pad_top(); + const int out_end_y = _output->info()->dimension(idx_h) - _info.pad_bottom() + _info.stride().second - 1; const int out_step_y = _info.stride().second; switch(data_layout) diff --git a/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp b/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp index 71218f5b52..69e5eff213 100644 --- a/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp +++ b/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp @@ -40,8 +40,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, con { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, input_info, weights_info); const DataLayout data_layout = input_info->data_layout(); - const unsigned int stride_x = deconv_info.stride().first; - const unsigned int stride_y = deconv_info.stride().second; const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); @@ -77,8 +75,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, con if(output->total_size() != 0) { - auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), - 0, 0, stride_x, stride_y); + const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second); + auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info); const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, *input_info, *weights_info); @@ -92,14 +90,11 @@ std::pair validate_and_configure_window(const ITensorInfo *input ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); const DataLayout data_layout = input_info->data_layout(); + const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second); - const unsigned int stride_x = deconv_info.stride().first; - const unsigned int stride_y = deconv_info.stride().second; - const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - - auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), - 0, 0, stride_x, stride_y); + auto out_dims = deconvolution_output_dimensions(input_info->dimension(idx_w), input_info->dimension(idx_h), weights_info->dimension(idx_w), weights_info->dimension(idx_h), stride_info); const TensorShape output_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, *input_info, *weights_info); diff --git a/src/core/CPP/kernels/CPPUpsampleKernel.cpp b/src/core/CPP/kernels/CPPUpsampleKernel.cpp index ad2d54a0f8..e63808f80e 100644 --- a/src/core/CPP/kernels/CPPUpsampleKernel.cpp +++ b/src/core/CPP/kernels/CPPUpsampleKernel.cpp @@ -76,10 +76,10 @@ void CPPUpsampleKernel::run(const Window &window, const ThreadInfo &info) const int height_scaled = _output->info()->dimension(1); const int stride_x = _info.stride().first; const int stride_y = _info.stride().second; - const int start_x = _info.pad().first; - const int start_y = _info.pad().second; - const int end_y = height_scaled - _info.pad().second; - const int end_x = width_scaled - _info.pad().first; + const int start_x = _info.pad_left(); + const int start_y = _info.pad_top(); + const int end_x = width_scaled - _info.pad_right(); + const int end_y = height_scaled - _info.pad_bottom(); const size_t element_size = _input->info()->element_size(); //The fill value is normally 0, but for QASYMM8 the '0' corresponds to the offset diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp index 122373f5c6..d11788acd3 100644 --- a/src/core/Utils.cpp +++ b/src/core/Utils.cpp @@ -374,15 +374,22 @@ PadStrideInfo arm_compute::calculate_same_pad(TensorShape input_shape, TensorSha return same_info; } -std::pair arm_compute::deconvolution_output_dimensions( - unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady, - unsigned int stride_x, unsigned int stride_y) +std::pair arm_compute::deconvolution_output_dimensions(unsigned int in_width, unsigned int in_height, + unsigned int kernel_width, unsigned int kernel_height, + const PadStrideInfo &pad_stride_info) { + const unsigned int pad_left = pad_stride_info.pad_left(); + const unsigned int pad_top = pad_stride_info.pad_top(); + const unsigned int pad_right = pad_stride_info.pad_right(); + const unsigned int pad_bottom = pad_stride_info.pad_bottom(); + const unsigned int stride_x = pad_stride_info.stride().first; + const unsigned int stride_y = pad_stride_info.stride().second; + ARM_COMPUTE_ERROR_ON(in_width < 1 || in_height < 1); - ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width) < 2 * padx); - ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height) < 2 * pady); - const int w = stride_x * (in_width - 1) + kernel_width - 2 * padx; - const int h = stride_y * (in_height - 1) + kernel_height - 2 * pady; + ARM_COMPUTE_ERROR_ON(((in_width - 1) * stride_x + kernel_width) < (pad_left + pad_right)); + ARM_COMPUTE_ERROR_ON(((in_height - 1) * stride_y + kernel_height) < (pad_top + pad_bottom)); + const int w = stride_x * (in_width - 1) + kernel_width - (pad_left + pad_right); + const int h = stride_y * (in_height - 1) + kernel_height - (pad_top + pad_bottom); return std::make_pair(w, h); } diff --git a/src/graph/nodes/DeconvolutionLayerNode.cpp b/src/graph/nodes/DeconvolutionLayerNode.cpp index 28c75297a5..d4a5b769e7 100644 --- a/src/graph/nodes/DeconvolutionLayerNode.cpp +++ b/src/graph/nodes/DeconvolutionLayerNode.cpp @@ -56,10 +56,7 @@ TensorDescriptor DeconvolutionLayerNode::compute_output_descriptor(const TensorD const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH); const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT); - std::tie(output_width, output_height) = deconvolution_output_dimensions(input_width, input_height, - kernel_width, kernel_height, - info.pad().first, info.pad().second, - info.stride().first, info.stride().second); + std::tie(output_width, output_height) = deconvolution_output_dimensions(input_width, input_height, kernel_width, kernel_height, info); const DataLayout data_layout = input_descriptor.layout; TensorDescriptor output_descriptor = input_descriptor; diff --git a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp index c1a39ef26a..b8089d8229 100644 --- a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp @@ -63,13 +63,8 @@ Status CLDirectDeconvolutionLayer::validate(const ITensorInfo *input, const ITen ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) != weights->dimension(idx_h)); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) < 1); - ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric()); - const unsigned int stride_x = info.stride().first; - const unsigned int stride_y = info.stride().second; - - auto out_dims = deconvolution_output_dimensions(input->dimension(idx_w), input->dimension(idx_h), weights->dimension(idx_w), weights->dimension(idx_h), - info.pad().first, info.pad().second, stride_x, stride_y); + auto out_dims = deconvolution_output_dimensions(input->dimension(idx_w), input->dimension(idx_h), weights->dimension(idx_w), weights->dimension(idx_h), info); const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input, *weights); @@ -92,9 +87,11 @@ Status CLDirectDeconvolutionLayer::validate(const ITensorInfo *input, const ITen ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(idx_h) != output_shape[idx_h], "Output's height is invalid."); ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(idx_c) != output_shape[idx_c], "Output's depth is invalid."); - unsigned int padx = 0; - unsigned int pady = 0; - const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, out_dims, padx, pady); + unsigned int deconv_pad_x = 0; + unsigned int deconv_pad_y = 0; + const unsigned int stride_x = info.stride().first; + const unsigned int stride_y = info.stride().second; + const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, out_dims, deconv_pad_x, deconv_pad_y); TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(scale_out_shape).set_data_layout(data_layout)); const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); @@ -109,6 +106,10 @@ void CLDirectDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + const unsigned int pad_left = info.pad_left(); + const unsigned int pad_right = info.pad_right(); + const unsigned int pad_top = info.pad_top(); + const unsigned int pad_bottom = info.pad_bottom(); const unsigned int stride_x = info.stride().first; const unsigned int stride_y = info.stride().second; @@ -122,8 +123,7 @@ void CLDirectDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, _weights_flipped.allocator()->init(weights->info()->clone()->set_data_layout(data_layout)); _flip_weights.configure(weights, &_weights_flipped, &_flip_axis); - auto out_dims = deconvolution_output_dimensions(input->info()->dimension(idx_w), input->info()->dimension(idx_h), weights->info()->dimension(idx_w), weights->info()->dimension(idx_h), - info.pad().first, info.pad().second, stride_x, stride_y); + auto out_dims = deconvolution_output_dimensions(input->info()->dimension(idx_w), input->info()->dimension(idx_h), weights->info()->dimension(idx_w), weights->info()->dimension(idx_h), info); const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input->info(), *weights->info()); @@ -138,16 +138,30 @@ void CLDirectDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, _memory_group.manage(&_scaled_output); // Find the upsampled dimensions and the padding needed for the convolution with stride 1 in order to match output shape - unsigned int padx = 0; - unsigned int pady = 0; - const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input->info(), *weights->info(), stride_x, stride_y, out_dims, padx, pady); + unsigned int deconv_pad_x = 0; + unsigned int deconv_pad_y = 0; + const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input->info(), *weights->info(), stride_x, stride_y, out_dims, deconv_pad_x, deconv_pad_y); + + unsigned int deconv_pad_left = pad_right > pad_left ? pad_right - pad_left : 0; + unsigned int deconv_pad_right = pad_left > pad_right ? pad_left - pad_right : 0; + deconv_pad_x -= deconv_pad_left + deconv_pad_right; + ARM_COMPUTE_ERROR_ON((deconv_pad_x % 2) != 0); + deconv_pad_left += deconv_pad_x / 2; + deconv_pad_right += deconv_pad_x / 2; + + unsigned int deconv_pad_top = pad_bottom > pad_top ? pad_bottom - pad_top : 0; + unsigned int deconv_pad_bottom = pad_top > pad_bottom ? pad_top - pad_bottom : 0; + deconv_pad_y -= deconv_pad_top + deconv_pad_bottom; + ARM_COMPUTE_ERROR_ON((deconv_pad_y % 2) != 0); + deconv_pad_top += deconv_pad_y / 2; + deconv_pad_bottom += deconv_pad_y / 2; TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->quantization_info()); scale_out_info.set_data_layout(data_layout); _scaled_output.allocator()->init(scale_out_info); // configure scale function - const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2); + const PadStrideInfo upsample_info(stride_x, stride_y, deconv_pad_left, deconv_pad_right, deconv_pad_top, deconv_pad_bottom, DimensionRoundingType::FLOOR); _scale_f.configure(input, &_scaled_output, upsample_info); // Setup the function to convolve the upscaled output diff --git a/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp index 36a120e4ef..78e1ae7f05 100644 --- a/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp @@ -151,8 +151,8 @@ Status CLGEMMDeconvolutionLayer::validate(const ITensorInfo *input, const ITenso ARM_COMPUTE_RETURN_ON_ERROR(CLGEMM::validate(&input->clone()->set_tensor_shape(nhwc_input_shape).set_is_resizable(true), &reshaped_t_info, nullptr, &gemm_output_info, 1.0f, 0.0f, gemm_info)); } - auto out_dims = deconvolution_output_dimensions(input->dimension(idx_w), input->dimension(idx_h), weights->dimension(idx_w), weights->dimension(idx_h), - 0, 0, deconv_info.stride().first, deconv_info.stride().second); + const PadStrideInfo stride_info(deconv_info.stride().first, deconv_info.stride().second); + auto out_dims = deconvolution_output_dimensions(input->dimension(idx_w), input->dimension(idx_h), weights->dimension(idx_w), weights->dimension(idx_h), stride_info); const TensorShape deconv_shape = misc::shape_calculator::compute_deconvolution_output_shape(out_dims, *input, *weights); TensorInfo col2im_output_info = gemm_output_info.clone()->set_tensor_shape(deconv_shape).set_is_resizable(true); diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index 1f2cc3d73b..bbb91b4651 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -64,13 +64,8 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf const unsigned int height_idx = get_data_layout_dimension_index(weights->data_layout(), DataLayoutDimension::HEIGHT); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(width_idx) != weights->dimension(height_idx)); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(width_idx) < 1); - ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric()); - const unsigned int stride_x = info.stride().first; - const unsigned int stride_y = info.stride().second; - - auto out_dims = deconvolution_output_dimensions(input->dimension(width_idx), input->dimension(height_idx), weights->dimension(width_idx), weights->dimension(height_idx), - info.pad().first, info.pad().second, stride_x, stride_y); + auto out_dims = deconvolution_output_dimensions(input->dimension(width_idx), input->dimension(height_idx), weights->dimension(width_idx), weights->dimension(height_idx), info); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); if(bias != nullptr) @@ -96,9 +91,11 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid."); } - unsigned int padx = 0; - unsigned int pady = 0; - const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, out_dims, padx, pady); + unsigned int deconv_pad_x = 0; + unsigned int deconv_pad_y = 0; + const unsigned int stride_x = info.stride().first; + const unsigned int stride_y = info.stride().second; + const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, out_dims, deconv_pad_x, deconv_pad_y); TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(scale_out_shape)); const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); @@ -126,14 +123,17 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _is_prepared = false; _is_nchw = data_layout == DataLayout::NCHW; + const unsigned int pad_left = info.pad_left(); + const unsigned int pad_right = info.pad_right(); + const unsigned int pad_top = info.pad_top(); + const unsigned int pad_bottom = info.pad_bottom(); const unsigned int stride_x = info.stride().first; const unsigned int stride_y = info.stride().second; const unsigned int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); const unsigned int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - auto out_dims = deconvolution_output_dimensions(input->info()->dimension(width_idx), input->info()->dimension(height_idx), weights->info()->dimension(width_idx), - weights->info()->dimension(height_idx), - info.pad().first, info.pad().second, stride_x, stride_y); + auto out_dims = deconvolution_output_dimensions(input->info()->dimension(width_idx), input->info()->dimension(height_idx), + weights->info()->dimension(width_idx), weights->info()->dimension(height_idx), info); const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input->info(), *weights->info()); // Output auto initialization if not yet initialized @@ -157,16 +157,30 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _permuted_weights.info()->set_data_layout(DataLayout::NCHW); // Find the upsampled dimensions and the padding needed for the convolution with stride 1 in order to match output shape - unsigned int padx = 0; - unsigned int pady = 0; - const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*_permuted_input.info(), *_permuted_weights.info(), stride_x, stride_y, out_dims, padx, - pady); + unsigned int deconv_pad_x = 0; + unsigned int deconv_pad_y = 0; + const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*_permuted_input.info(), *_permuted_weights.info(), stride_x, stride_y, out_dims, + deconv_pad_x, deconv_pad_y); + + unsigned int deconv_pad_left = pad_right > pad_left ? pad_right - pad_left : 0; + unsigned int deconv_pad_right = pad_left > pad_right ? pad_left - pad_right : 0; + deconv_pad_x -= deconv_pad_left + deconv_pad_right; + ARM_COMPUTE_ERROR_ON((deconv_pad_x % 2) != 0); + deconv_pad_left += deconv_pad_x / 2; + deconv_pad_right += deconv_pad_x / 2; + + unsigned int deconv_pad_top = pad_bottom > pad_top ? pad_bottom - pad_top : 0; + unsigned int deconv_pad_bottom = pad_top > pad_bottom ? pad_top - pad_bottom : 0; + deconv_pad_y -= deconv_pad_top + deconv_pad_bottom; + ARM_COMPUTE_ERROR_ON((deconv_pad_y % 2) != 0); + deconv_pad_top += deconv_pad_y / 2; + deconv_pad_bottom += deconv_pad_y / 2; TensorInfo scale_out_info(scale_out_shape, 1, _permuted_input.info()->data_type(), _permuted_input.info()->quantization_info()); scale_out_info.set_data_layout(DataLayout::NCHW); _scaled_output.allocator()->init(scale_out_info); - const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2); + const PadStrideInfo upsample_info(stride_x, stride_y, deconv_pad_left, deconv_pad_right, deconv_pad_top, deconv_pad_bottom, DimensionRoundingType::FLOOR); _upsample_f.configure(&_permuted_input, &_scaled_output, upsample_info); _weights_flipped.allocator()->init(*_permuted_weights.info()->clone()); @@ -189,14 +203,30 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con else { // Find the upsampled dimensions and the padding needed for the convolution with stride 1 in order to match output shape - unsigned int padx = 0; - unsigned int pady = 0; - const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input->info(), *weights->info(), stride_x, stride_y, out_dims, padx, pady); + unsigned int deconv_pad_x = 0; + unsigned int deconv_pad_y = 0; + const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input->info(), *weights->info(), stride_x, stride_y, + out_dims, deconv_pad_x, deconv_pad_y); + + unsigned int deconv_pad_left = pad_right > pad_left ? pad_right - pad_left : 0; + unsigned int deconv_pad_right = pad_left > pad_right ? pad_left - pad_right : 0; + deconv_pad_x -= deconv_pad_left + deconv_pad_right; + ARM_COMPUTE_ERROR_ON((deconv_pad_x % 2) != 0); + deconv_pad_left += deconv_pad_x / 2; + deconv_pad_right += deconv_pad_x / 2; + + unsigned int deconv_pad_top = pad_bottom > pad_top ? pad_bottom - pad_top : 0; + unsigned int deconv_pad_bottom = pad_top > pad_bottom ? pad_top - pad_bottom : 0; + deconv_pad_y -= deconv_pad_top + deconv_pad_bottom; + ARM_COMPUTE_ERROR_ON((deconv_pad_y % 2) != 0); + deconv_pad_top += deconv_pad_y / 2; + deconv_pad_bottom += deconv_pad_y / 2; TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->quantization_info()); scale_out_info.set_data_layout(data_layout); _scaled_output.allocator()->init(scale_out_info); - const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2); + + const PadStrideInfo upsample_info(stride_x, stride_y, deconv_pad_left, deconv_pad_right, deconv_pad_top, deconv_pad_bottom, DimensionRoundingType::FLOOR); _upsample_f.configure(input, &_scaled_output, upsample_info); _weights_flipped.allocator()->init(weights->info()->clone()->set_data_layout(data_layout)); -- cgit v1.2.1