COMPMID-2092: Refactoring interface for the deconvolution kernels (NEON/CL)
3RDPARTY_UPDATE
Change-Id: Id7ddf97e2c9ceb2cb84084fab2c6f5697890c193
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1424
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
index c3d6b94..7bbacb1 100644
--- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp
@@ -43,13 +43,11 @@
_original_weights(nullptr),
_input(nullptr),
_info(),
- _inner_border(),
_is_prepared(false)
{
}
-Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info,
- unsigned int inner_border_right, unsigned int inner_border_top)
+Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16, DataType::QASYMM8);
@@ -61,9 +59,6 @@
const unsigned int stride_x = info.stride().first;
const unsigned int stride_y = info.stride().second;
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_right > stride_x - 1, "inner_border_right must be smaller than stride_x");
- 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, stride_x, stride_y);
@@ -91,7 +86,7 @@
unsigned int padx = 0;
unsigned int pady = 0;
- const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, inner_border_right, inner_border_top, out_dims, padx, pady);
+ const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input, *weights, stride_x, stride_y, out_dims, padx, pady);
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);
@@ -105,15 +100,13 @@
return Status{};
}
-void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info,
- unsigned int inner_border_right, unsigned int inner_border_top)
+void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
_input = input;
_original_weights = weights;
_info = info;
- _inner_border = std::make_pair(inner_border_right, inner_border_top);
_is_prepared = false;
const DataLayout data_layout = input->info()->data_layout();
@@ -131,35 +124,26 @@
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));
+ ARM_COMPUTE_ERROR_THROW_ON(NEDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info));
_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, inner_border_right, inner_border_top, out_dims, padx, pady);
+ const TensorShape scale_out_shape = compute_deconvolution_upsampled_shape(*input->info(), *weights->info(), stride_x, stride_y, out_dims, padx, pady);
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);
+ _upsample_f.configure(input, &_scaled_output, upsample_info);
// 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_flipped, bias, output, conv_info);
_scaled_output.allocator()->allocate();
}
-Status NEDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info)
-{
- return NEDeconvolutionLayer::validate(input, weights, bias, output, info, 0, 0);
-}
-
-void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info)
-{
- configure(input, weights, bias, output, info, 0, 0);
-}
void NEDeconvolutionLayer::run()
{
@@ -193,4 +177,4 @@
_is_prepared = true;
}
}
-} // namespace arm_compute
\ No newline at end of file
+} // namespace arm_compute