diff options
Diffstat (limited to 'src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp')
-rw-r--r-- | src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp | 22 |
1 files changed, 14 insertions, 8 deletions
diff --git a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp index c01588a164..ee76248e35 100644 --- a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "arm_compute/runtime/CPP/CPPScheduler.h" #include "utils/TypePrinter.h" #include <memory> @@ -46,6 +45,7 @@ CLDirectDeconvolutionLayer::CLDirectDeconvolutionLayer(std::shared_ptr<IMemoryMa _scaled_output(), _original_weights(nullptr), _weights_flipped(), + _flip_axis(), _is_prepared(false) { } @@ -120,8 +120,9 @@ void CLDirectDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, const size_t idx_h = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); _original_weights = weights; + _flip_axis.allocator()->init(TensorInfo(TensorShape(2U), 1, DataType::U32)); _weights_flipped.allocator()->init(weights->info()->clone()->set_data_layout(data_layout)); - _flip_weights.configure(weights, &_weights_flipped); + _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); @@ -151,10 +152,18 @@ void CLDirectDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, const PadStrideInfo upsample_info(stride_x, stride_y, padx / 2, pady / 2); _scale_f.configure(input, &_scaled_output, BorderSize(), upsample_info); - // setup the function to convolve the upscaled output + // 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, weights_info); _scaled_output.allocator()->allocate(); + + // Setup flip axis data + _flip_axis.allocator()->allocate(); + _flip_axis.map(true); + auto axis_data = reinterpret_cast<uint32_t *>(_flip_axis.buffer()); + axis_data[0] = 0; + axis_data[1] = 1; + _flip_axis.unmap(); } void CLDirectDeconvolutionLayer::run() @@ -177,16 +186,13 @@ void CLDirectDeconvolutionLayer::prepare() // Run weights flipping and mark original weights tensor as unused _weights_flipped.allocator()->allocate(); - _weights_flipped.map(true); - _original_weights->map(CLScheduler::get().queue(), true); - CPPScheduler::get().schedule(&_flip_weights, Window::DimZ); - _weights_flipped.unmap(); - _original_weights->unmap(CLScheduler::get().queue()); + _flip_weights.run(); _original_weights->mark_as_unused(); // Prepare convolution _conv_f.prepare(); + // Free flipped weights if(!_weights_flipped.is_used()) { _weights_flipped.allocator()->free(); |