From afbc5ffb0b567ae93fa2765066bd136d72be88ff Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Wed, 3 Oct 2018 14:18:19 +0100 Subject: COMPMID-1621 Deconvolution wrong output calculation Change-Id: Ida71312bcf6dbd854f2ab1efc65f74910c79e152 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/151510 Tested-by: bsgcomp Reviewed-by: Michele DiGiorgio --- .../NEON/functions/NEDeconvolutionLayer.cpp | 50 ++++++++++++++++------ 1 file changed, 37 insertions(+), 13 deletions(-) (limited to 'src/runtime/NEON/functions/NEDeconvolutionLayer.cpp') diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index fda9f57499..6ca60c66a4 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -27,6 +27,7 @@ #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/runtime/CPP/CPPScheduler.h" using namespace arm_compute; using namespace arm_compute::misc::shape_calculator; @@ -35,7 +36,9 @@ NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr memor : _memory_group(std::move(memory_manager)), _conv_f(), _upsample_f(), + _flip_weights(), _scaled_output(), + _weights_flipped(), _input(nullptr), _info(), _inner_border(), @@ -60,7 +63,7 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_top > stride_y - 1, "inner_border_top must be smaller than stride_y"); auto out_dims = deconvolution_output_dimensions(input->dimension(0), input->dimension(1), weights->dimension(0), weights->dimension(1), - info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y); + info.pad().first, info.pad().second, stride_x, stride_y); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, bias); @@ -74,14 +77,14 @@ Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape()); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid."); ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid."); ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid."); } - TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, stride_x, stride_y, inner_border_right, inner_border_top, - info))); + TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, *weights, stride_x, stride_y, inner_border_right, + inner_border_top, + out_dims))); const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) @@ -107,25 +110,44 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con const unsigned int stride_x = info.stride().first; const unsigned int stride_y = info.stride().second; + _weights_flipped.allocator()->init(TensorInfo(weights->info()->tensor_shape(), 1, weights->info()->data_type())); + _flip_weights.configure(weights, &_weights_flipped); + + auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), + info.pad().first, info.pad().second, stride_x, stride_y); + + const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); + // Output auto initialization if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info()); + // Perform validation step ARM_COMPUTE_ERROR_THROW_ON(NEDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top)); _memory_group.manage(&_scaled_output); - // configure scale function - // Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor - const TensorInfo scale_out_info(compute_deconvolution_shape(*input->info(), stride_x, stride_y, inner_border_right, inner_border_top, info), 1, input->info()->data_type()); + // Find the upsampled dimensions + unsigned int out_x = (input->info()->dimension(0) - 1) * stride_x + inner_border_right + 1; + unsigned int out_y = (input->info()->dimension(1) - 1) * stride_y + inner_border_top + 1; + + // Find the padding needed for the convolution with stride 1 in order to match output shape + unsigned int padx = out_dims.first - (out_x - weights->info()->dimension(0) + 1); + unsigned int pady = out_dims.second - (out_y - weights->info()->dimension(1) + 1); + out_x += padx; + out_y += pady; + + TensorShape scale_out_shape(input->info()->tensor_shape()); + scale_out_shape.set(0, out_x); + scale_out_shape.set(1, out_y); + TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->quantization_info()); _scaled_output.allocator()->init(scale_out_info); + const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2); + _upsample_f.configure(input, &_scaled_output, upsample_info, inner_border_right, inner_border_top); + // setup the function to convolve the upscaled output const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); - _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); - - // Allocate auxiliary tensors + _conv_f.configure(&_scaled_output, &_weights_flipped, bias, output, conv_info); _scaled_output.allocator()->allocate(); - - // configure upsample function - _upsample_f.configure(input, &_scaled_output, info, inner_border_right, inner_border_top); } void NEDeconvolutionLayer::run() @@ -144,6 +166,8 @@ void NEDeconvolutionLayer::prepare() { if(!_is_prepared) { + _weights_flipped.allocator()->allocate(); + CPPScheduler::get().schedule(&_flip_weights, Window::DimZ); _conv_f.prepare(); _is_prepared = true; } -- cgit v1.2.1