COMPMID-2605: Add asymmetric padding support for Deconvolution layer
Change-Id: I63b773bdce25f1342ccd3a08ded623a1508f70fe
Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1797
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
diff --git a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
index c1a39ef..b8089d8 100644
--- a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
@@ -63,13 +63,8 @@
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 @@
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 @@
{
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 @@
_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 @@
_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 36a120e..78e1ae7 100644
--- a/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp
@@ -151,8 +151,8 @@
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);