From 7891a73ef36f4ad7b71069b3c57694f85bb79454 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Fri, 20 Aug 2021 21:39:25 +0100 Subject: Move CPU/GPU files from Core/Runtime to the respective backend folders Legacy structure contained two libraries core/runtime with two backends in each. We reduce the core/runtime libraries to a single library thus merging the backend files Signed-off-by: Georgios Pinitas Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155 Comments-Addressed: Arm Jenkins Reviewed-by: Michele Di Giorgio Tested-by: Arm Jenkins --- src/cpu/operators/CpuDirectConv2d.cpp | 147 ++++++++++++++++++++++++++++++++++ 1 file changed, 147 insertions(+) create mode 100644 src/cpu/operators/CpuDirectConv2d.cpp (limited to 'src/cpu/operators/CpuDirectConv2d.cpp') diff --git a/src/cpu/operators/CpuDirectConv2d.cpp b/src/cpu/operators/CpuDirectConv2d.cpp new file mode 100644 index 0000000000..ec52dbf153 --- /dev/null +++ b/src/cpu/operators/CpuDirectConv2d.cpp @@ -0,0 +1,147 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "src/cpu/operators/CpuDirectConv2d.h" + +#include "arm_compute/core/PixelValue.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" + +namespace arm_compute +{ +namespace cpu +{ +CpuDirectConv2d::~CpuDirectConv2d() = default; + +CpuDirectConv2d::CpuDirectConv2d(std::shared_ptr memory_manager) + : _memory_group(std::move(memory_manager)), _output_stage_kernel(), _conv_kernel(), _input_border_handler(), _activationlayer_function(), _accumulator(), _has_bias(false), + _is_activationlayer_enabled(false), _dim_split(Window::DimZ), _is_padding_required() +{ +} + +void CpuDirectConv2d::configure(ITensorInfo *src, ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON(src->data_layout() == DataLayout::UNKNOWN); + _output_stage_kernel = std::make_unique(); + _conv_kernel = std::make_unique(); + _input_border_handler = std::make_unique(); + + // Free accumulator + if(_accumulator.buffer() != nullptr) + { + _accumulator.allocator()->free(); + } + + _dim_split = src->data_layout() == DataLayout::NCHW ? Window::DimZ : Window::DimY; + + // Check if bias should be added in the convolution result + _has_bias = (bias != nullptr); + + _conv_kernel->configure(src, weights, dst, conv_info); + if(_has_bias) + { + _output_stage_kernel->configure(dst, bias); + } + _is_padding_required = !_conv_kernel->border_size().empty(); + + if(_is_padding_required) + { + // Add zero padding XY + _input_border_handler->configure(src, _conv_kernel->border_size(), BorderMode::CONSTANT, PixelValue(static_cast(0.f))); + } + + //Configure Activation Layer + _is_activationlayer_enabled = act_info.enabled(); + if(_is_activationlayer_enabled) + { + _activationlayer_function = std::make_unique(); + _activationlayer_function->configure(dst, dst, act_info); + } +} + +Status CpuDirectConv2d::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *dst, const PadStrideInfo &conv_info, + const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, weights, dst); + + // output might not be initialized since it can be an intermediate tensor of another layer + DataType data_type = src->data_type(); + TensorInfo accumulator(dst->clone()->set_is_resizable(true).reset_padding().set_data_type(data_type)); + + // Validate Convolution kernel + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuDirectConv2dKernel::validate(src, weights, &accumulator, conv_info)); + + if(bias != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, bias); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->dimension(0) != weights->dimension(3), + "Biases size and number of input feature maps should match"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->num_dimensions() > 1, "Biases should be one dimensional"); + } + + // Validate bias kernel + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuDirectConv2dOutputStageKernel::validate(&accumulator, bias, dst)); + + if(act_info.enabled()) + { + ARM_COMPUTE_RETURN_ON_ERROR(CpuActivation::validate(dst, nullptr, act_info)); + } + + return Status{}; +} + +void CpuDirectConv2d::run(ITensorPack &tensors) +{ + MemoryGroupResourceScope scope_mg(_memory_group); + + auto src = tensors.get_tensor(TensorType::ACL_SRC_0); + auto bias = tensors.get_const_tensor(TensorType::ACL_SRC_2); + auto dst = tensors.get_tensor(TensorType::ACL_DST); + + if(_is_padding_required) + { + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC_DST, src); + NEScheduler::get().schedule_op(_input_border_handler.get(), Window::DimZ, _input_border_handler->window(), pack); + } + NEScheduler::get().schedule_op(_conv_kernel.get(), _dim_split, _conv_kernel->window(), tensors); + if(_has_bias) + { + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC_0, dst); + pack.add_tensor(TensorType::ACL_SRC_1, bias); + pack.add_tensor(TensorType::ACL_DST, dst); + NEScheduler::get().schedule_op(_output_stage_kernel.get(), Window::DimY, _output_stage_kernel->window(), pack); + } + + if(_is_activationlayer_enabled) + { + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC, dst); + pack.add_tensor(TensorType::ACL_DST, dst); + _activationlayer_function->run(pack); + } +} +} // namespace cpu +} // namespace arm_compute -- cgit v1.2.1