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 --- .../kernels/CLDeconvolutionLayerUpsampleKernel.cpp | 79 ++++++++++++++++------ src/core/CPP/kernels/CPPFlipWeightsKernel.cpp | 27 +++++--- src/core/Utils.cpp | 9 --- src/runtime/CL/functions/CLDeconvolutionLayer.cpp | 60 +++++++++------- .../NEON/functions/NEDeconvolutionLayer.cpp | 30 ++++---- 5 files changed, 123 insertions(+), 82 deletions(-) (limited to 'src') diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp index be3a926b96..dd7d79002d 100644 --- a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp +++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp @@ -45,11 +45,19 @@ Status CLDeconvolutionLayerUpsampleKernel::validate(const ITensorInfo *input, co ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) == 0); - ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) == 0); + + 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(output->dimension(idx_w) == 0); + ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(idx_h) == 0); ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric()); - for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_c) != output->dimension(idx_c)); + for(size_t i = 3; i < Coordinates::num_max_dimensions; ++i) { ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(i) != output->dimension(i)); } @@ -93,28 +101,61 @@ void CLDeconvolutionLayerUpsampleKernel::run(const Window &window, cl::CommandQu ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + 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); + const int out_start_x = _info.pad().first; - const int out_end_x = _output->info()->dimension(0) - _inner_border.right - _info.pad().first + _info.stride().first - 1; + const int out_end_x = _output->info()->dimension(idx_w) - _inner_border.right - _info.pad().first + _info.stride().first - 1; const int out_step_x = _info.stride().first; const int out_start_y = _inner_border.top + _info.pad().second; - const int out_end_y = _output->info()->dimension(1) - _info.pad().second + _info.stride().second - 1; + const int out_end_y = _output->info()->dimension(idx_h) - _info.pad().second + _info.stride().second - 1; const int out_step_y = _info.stride().second; - Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - - Window slice_out = collapsed.first_slice_window_3D(); - slice_out.set(Window::DimX, Window::Dimension(out_start_x, out_end_x, out_step_x)); - slice_out.set(Window::DimY, Window::Dimension(out_start_y, out_end_y, out_step_y)); - - Window slice_in = collapsed.first_slice_window_3D(); - - do + switch(data_layout) { - unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, slice_in); - add_3D_tensor_argument(idx, _output, slice_out); - enqueue(queue, *this, slice_out); + case DataLayout::NCHW: + { + Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); + + Window slice_out = collapsed.first_slice_window_3D(); + slice_out.set(Window::DimX, Window::Dimension(out_start_x, out_end_x, out_step_x)); + slice_out.set(Window::DimY, Window::Dimension(out_start_y, out_end_y, out_step_y)); + + Window slice_in = collapsed.first_slice_window_3D(); + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice_in); + add_3D_tensor_argument(idx, _output, slice_out); + enqueue(queue, *this, slice_out); + } + while(collapsed.slide_window_slice_3D(slice_in) && collapsed.slide_window_slice_3D(slice_out)); + break; + } + case DataLayout::NHWC: + { + // NOTE: not collapsing in NHWC + Window slice_out = window.first_slice_window_3D(); + slice_out.set(Window::DimY, Window::Dimension(out_start_x, out_end_x, out_step_x)); + slice_out.set(Window::DimZ, Window::Dimension(out_start_y, out_end_y, out_step_y)); + + Window slice_in = window.first_slice_window_3D(); + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice_in); + add_3D_tensor_argument(idx, _output, slice_out); + enqueue(queue, *this, slice_out); + } + while(window.slide_window_slice_3D(slice_in) && window.slide_window_slice_3D(slice_out)); + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported data layout"); } - while(collapsed.slide_window_slice_3D(slice_in) && collapsed.slide_window_slice_3D(slice_out)); } diff --git a/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp b/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp index 741218e4f7..2d4c0ce5c8 100644 --- a/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp +++ b/src/core/CPP/kernels/CPPFlipWeightsKernel.cpp @@ -42,25 +42,36 @@ CPPFlipWeightsKernel::CPPFlipWeightsKernel() } template -void CPPFlipWeightsKernel::flip_weights(const Window &window_input, const Window &window) +void CPPFlipWeightsKernel::flip_weights(const Window &window_input) { // Create iterators Iterator in(_input, window_input); - Iterator out(_output, window); + 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); - const int kernel_size = _input->info()->dimension(0); + const int kernel_width = _input->info()->dimension(idx_w); + const int kernel_height = _input->info()->dimension(idx_h); execute_window_loop(window_input, [&](const Coordinates & id) { - *((reinterpret_cast(out.ptr()) + kernel_size * (kernel_size - id.y() - 1) + (kernel_size - id.x() - 1))) = *(reinterpret_cast(in.ptr())); + const unsigned int x = kernel_width - id[idx_w] - 1; + const unsigned int y = kernel_height - id[idx_h] - 1; + Coordinates output_coord(id); + output_coord.set(idx_w, x); + output_coord.set(idx_h, y); + *(reinterpret_cast(_output->ptr_to_element(output_coord))) = *(reinterpret_cast(in.ptr())); }, - in, out); + in); } void CPPFlipWeightsKernel::configure(const ITensor *input, ITensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); _input = input; _output = output; @@ -98,9 +109,5 @@ void CPPFlipWeightsKernel::run(const Window &window, const ThreadInfo &info) ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window); ARM_COMPUTE_ERROR_ON(_func == nullptr); - Window out_window{ window }; - out_window.set(Window::DimX, Window::Dimension(0, 0, 0)); - out_window.set(Window::DimY, Window::Dimension(0, 0, 0)); - - (this->*_func)(window, out_window); + (this->*_func)(window); } diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp index a6a5771ec1..41fc87e87a 100644 --- a/src/core/Utils.cpp +++ b/src/core/Utils.cpp @@ -323,15 +323,6 @@ PadStrideInfo arm_compute::calculate_same_pad(TensorShape input_shape, TensorSha return PadStrideInfo(strides.first, strides.second, same_pad_left, same_pad_right, same_pad_top, same_pad_bottom, DimensionRoundingType::CEIL); } -TensorShape arm_compute::deconvolution_output_shape(const std::pair &out_dims, TensorShape input, TensorShape weights) -{ - TensorShape out_shape(input); - out_shape.set(0, out_dims.first); - out_shape.set(1, out_dims.second); - out_shape.set(2, weights[3]); - return out_shape; -} - const std::pair arm_compute::deconvolution_output_dimensions( unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady, unsigned int stride_x, unsigned int stride_y) 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 diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp index 6ca60c66a4..cbe7c51662 100644 --- a/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDeconvolutionLayer.cpp @@ -76,15 +76,17 @@ 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()); + const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input, *weights); + 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, *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)); const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) @@ -116,7 +118,7 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con 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()); + 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()); @@ -125,19 +127,11 @@ void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, con _memory_group.manage(&_scaled_output); - // 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()); _scaled_output.allocator()->init(scale_out_info); @@ -171,4 +165,4 @@ void NEDeconvolutionLayer::prepare() _conv_f.prepare(); _is_prepared = true; } -} \ No newline at end of file +} -- cgit v1.2.1