From ed5a492ba791d8c8b3334749d4ae946b8f11d13d Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Thu, 13 Sep 2018 16:22:01 +0100 Subject: COMPMID-1586: Add support for NHWC CLDeconvolutionLayer COMPMID-1651: Fix QASYMM8 CLDeconvolutionLayer This patch also extends the range of values used for testing Convolution and Deconvolution to cover quantized [-1.0f, 1.0f]. Change-Id: I8b280669db67bb3ec25bf5d411c8f5954f5b0dab Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/149869 Reviewed-by: Michalis Spyrou Tested-by: bsgcomp --- src/runtime/CL/functions/CLDeconvolutionLayer.cpp | 60 +++++++++++++---------- 1 file changed, 34 insertions(+), 26 deletions(-) (limited to 'src/runtime/CL/functions/CLDeconvolutionLayer.cpp') diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp index 26d44e9c96..951d1ec4f0 100644 --- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp @@ -53,8 +53,16 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != weights->dimension(1)); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) < 1); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, weights); + + const DataLayout data_layout = input->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 size_t idx_c = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); + + 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; @@ -63,10 +71,10 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf 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), + 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); - const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape()); + const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input, *weights); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights); @@ -80,15 +88,17 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); } + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, bias); } - 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."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(idx_w) != output_shape[idx_w], "Output's width is invalid."); + 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."); - 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))); + 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); + 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); ARM_COMPUTE_RETURN_ON_ERROR(CLDeconvolutionLayerUpsample::validate(input, &scale_out_info, BorderSize(inner_border_right, inner_border_top), info)); @@ -105,17 +115,22 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, const const unsigned int stride_x = info.stride().first; const unsigned int stride_y = info.stride().second; + 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); + _weights = weights; - _weights_flipped.allocator()->init(TensorInfo(weights->info()->tensor_shape(), 1, weights->info()->data_type())); + _weights_flipped.allocator()->init(weights->info()->clone()->set_data_layout(data_layout)); _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), + 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); - const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); + const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input->info(), *weights->info()); // Output auto initialization if not yet initialized - auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info()); + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_layout(data_layout)); // Perform validation step ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top)); @@ -125,20 +140,13 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, ICLTensor *weights, const _memory_group.manage(&_scaled_output); _memory_group.manage(&_weights_flipped); - // 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; + // 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); - 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()); + scale_out_info.set_data_layout(data_layout); _scaled_output.allocator()->init(scale_out_info); // configure scale function -- cgit v1.2.1