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Diffstat (limited to 'runtime/neurun/backend/srcn/KernelGenerator.cc')
| -rw-r--r-- | runtime/neurun/backend/srcn/KernelGenerator.cc | 275 |
1 files changed, 0 insertions, 275 deletions
diff --git a/runtime/neurun/backend/srcn/KernelGenerator.cc b/runtime/neurun/backend/srcn/KernelGenerator.cc deleted file mode 100644 index c096f9230..000000000 --- a/runtime/neurun/backend/srcn/KernelGenerator.cc +++ /dev/null @@ -1,275 +0,0 @@ -/* - * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "KernelGenerator.h" - -#include <stdexcept> - -#include "cpp14/memory.h" -#include "util/Padding.h" -#include "kernel/ConvolutionLayer.h" -#include "kernel/DepthwiseConvolutionLayer.h" -#include "kernel/InstanceNormLayer.h" -#include "kernel/TransposeConvLayer.h" -#include "kernel/AddLayer.h" - -#include <backend/Backend.h> -#include <backend/IConfig.h> - -#include "util/logging.h" - -#include "util/Utils.h" - -namespace neurun -{ -namespace backend -{ -namespace srcn -{ - -KernelGenerator::KernelGenerator(const ir::Operands &operand_ctx, - const std::shared_ptr<TensorBuilder> &tensor_builder, - const std::shared_ptr<custom::IKernelBuilder> &kb) - : _ctx(operand_ctx), _tensor_builder(tensor_builder), _kernel_builder(kb), - _current_subg_layout(ir::Layout::UNKNOWN) -{ - // DO NOTHING -} - -void KernelGenerator::visit(const ir::OpSequence &op_seq) -{ - _current_subg_layout = op_seq.getLayout(); - for (const auto &e : op_seq.operations()) - { - const auto &node = *(e.node); - _tensor_builder->preVisit(node); - node.accept(*this); - _tensor_builder->postVisit(node); - } -} - -void KernelGenerator::visit(const ir::operation::Conv2D &node) -{ - using ir::operation::Conv2D; - - const auto ofm_index{node.getOutputs().at(0)}; - const auto ifm_index{node.getInputs().at(Conv2D::Input::INPUT)}; - const auto ker_index{node.getInputs().at(Conv2D::Input::KERNEL)}; - const auto bias_index{node.getInputs().at(Conv2D::Input::BIAS)}; - - const auto ifm_shape = _ctx.at(ifm_index).shape().asFeature(_current_subg_layout); - const auto ofm_shape = _ctx.at(ofm_index).shape().asFeature(_current_subg_layout); - // Kernel format is [depth_out, kernel_height, kernel_width, depth_in] if NHWC and [depth_out, - // depth_in, kernel_height, kernel_width] if NCHW. - const auto &ker_shape = _ctx.at(ker_index).shape().asFeature(_current_subg_layout); - const auto ker_height = ker_shape.H; - const auto ker_width = ker_shape.W; - const auto stride = node.param().stride; - const auto padding = neurun::util::calculatePadding(node.param().padding, ifm_shape, ofm_shape, - stride, ker_width, ker_height); - const int has_padding = padding.left + padding.right + padding.top + padding.bottom; - - auto ofm_alloc = _tensor_builder->at(ofm_index); - auto ifm_alloc = _tensor_builder->at(ifm_index); - auto ker_alloc = _tensor_builder->at(ker_index); - auto bias_alloc = _tensor_builder->at(bias_index); - const auto backend_layout = ifm_alloc->layout(); - assert(backend_layout == ofm_alloc->layout()); - - const auto ofm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ofm_index), _current_subg_layout, backend_layout); - const auto ifm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ifm_index), _current_subg_layout, backend_layout); - const auto ker_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ker_index), _current_subg_layout, backend_layout); - const auto bias_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(bias_index), _current_subg_layout, backend_layout); - - auto fn = nnfw::cpp14::make_unique<::neurun::backend::srcn::kernel::ConvolutionLayer>(); - - // TODO Support activation - fn->configure(ifm_alloc->buffer(), ifm_backend_descr, ker_alloc->buffer(), ker_backend_descr, - bias_alloc->buffer(), bias_backend_descr, has_padding, padding.left, padding.right, - padding.top, padding.bottom, stride.horizontal, stride.vertical, - /*activation,*/ ofm_alloc->buffer(), ofm_backend_descr, backend_layout); - - _execution_builder->append(std::move(fn)); -} - -void KernelGenerator::visit(const ir::operation::InstanceNorm &node) -{ - using ir::operation::InstanceNorm; - - const auto ofm_index{node.getOutputs().at(0)}; - const auto ifm_index{node.getInputs().at(InstanceNorm::Input::INPUT)}; - const auto gamma_index{node.getInputs().at(InstanceNorm::Input::GAMMA)}; - const auto beta_index{node.getInputs().at(InstanceNorm::Input::BETA)}; - - const auto epsilon = node.param().epsilon; - const auto activation = node.param().activation; - - auto ofm_alloc = _tensor_builder->at(ofm_index); - auto ifm_alloc = _tensor_builder->at(ifm_index); - auto gamma_alloc = _tensor_builder->at(gamma_index); - auto beta_alloc = _tensor_builder->at(beta_index); - - const auto backend_layout = ofm_alloc->layout(); - - const auto ofm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ofm_index), _current_subg_layout, backend_layout); - const auto ifm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ifm_index), _current_subg_layout, backend_layout); - const auto gamma_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(gamma_index), _current_subg_layout, backend_layout); - const auto beta_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(beta_index), _current_subg_layout, backend_layout); - - auto fn = nnfw::cpp14::make_unique<::neurun::backend::srcn::kernel::InstanceNormLayer>(); - - fn->configure(ifm_alloc->buffer(), ifm_backend_descr, gamma_alloc->buffer(), gamma_backend_descr, - beta_alloc->buffer(), beta_backend_descr, ofm_alloc->buffer(), ofm_backend_descr, - epsilon, activation, backend_layout); - - _execution_builder->append(std::move(fn)); -} - -void KernelGenerator::visit(const ir::operation::DepthwiseConv2D &node) -{ - using ir::operation::DepthwiseConv2D; - - const auto ofm_index{node.getOutputs().at(0)}; - const auto ifm_index{node.getInputs().at(DepthwiseConv2D::Input::INPUT)}; - const auto ker_index{node.getInputs().at(DepthwiseConv2D::Input::KERNEL)}; - const auto bias_index{node.getInputs().at(DepthwiseConv2D::Input::BIAS)}; - - const auto ifm_shape = _ctx.at(ifm_index).shape().asFeature(_current_subg_layout); - const auto ofm_shape = _ctx.at(ofm_index).shape().asFeature(_current_subg_layout); - // Kernel format is [depth_out, kernel_height, kernel_width, depth_in] if NHWC and [depth_out, - // depth_in, kernel_height, kernel_width] if NCHW. - const auto &ker_shape = _ctx.at(ker_index).shape().asFeature(_current_subg_layout); - const auto ker_height = ker_shape.H; - const auto ker_width = ker_shape.W; - const auto stride = node.param().stride; - const auto padding = neurun::util::calculatePadding(node.param().padding, ifm_shape, ofm_shape, - stride, ker_width, ker_height); - const int padding_type = padding.left + padding.right + padding.top + padding.bottom; - - auto ofm_alloc = _tensor_builder->at(ofm_index); - auto ifm_alloc = _tensor_builder->at(ifm_index); - auto ker_alloc = _tensor_builder->at(ker_index); - auto bias_alloc = _tensor_builder->at(bias_index); - const auto backend_layout = ifm_alloc->layout(); - assert(backend_layout == ofm_alloc->layout()); - - const auto ofm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ofm_index), _current_subg_layout, backend_layout); - const auto ifm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ifm_index), _current_subg_layout, backend_layout); - const auto ker_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ker_index), _current_subg_layout, backend_layout); - const auto bias_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(bias_index), _current_subg_layout, backend_layout); - - auto fn = nnfw::cpp14::make_unique<::neurun::backend::srcn::kernel::DepthwiseConvolutionLayer>(); - - // TODO Support activation - fn->configure(ifm_alloc->buffer(), ifm_backend_descr, ker_alloc->buffer(), ker_backend_descr, - bias_alloc->buffer(), bias_backend_descr, padding_type, padding.left, padding.right, - padding.top, padding.bottom, stride.horizontal, stride.vertical, - /*activation,*/ ofm_alloc->buffer(), ofm_backend_descr, backend_layout); - - _execution_builder->append(std::move(fn)); -} - -void KernelGenerator::visit(const ir::operation::TransposeConv &node) -{ - using ir::operation::TransposeConv; - - const auto ofm_index{node.getOutputs().at(0)}; - const auto ifm_index{node.getInputs().at(TransposeConv::Input::INPUT)}; - const auto ker_index{node.getInputs().at(TransposeConv::Input::KERNEL)}; - const auto output_shape_index{node.getInputs().at(TransposeConv::Input::OUTPUT_SHAPE)}; - - const auto ifm_shape = _ctx.at(ifm_index).shape().asFeature(_current_subg_layout); - const auto ofm_shape = _ctx.at(ofm_index).shape().asFeature(_current_subg_layout); - // Kernel format is [depth_out, kernel_height, kernel_width, depth_in] if NHWC and [depth_out, - // depth_in, kernel_height, kernel_width] if NCHW. - const auto &ker_shape = _ctx.at(ker_index).shape().asFeature(_current_subg_layout); - const auto ker_height = ker_shape.H; - const auto ker_width = ker_shape.W; - const auto stride = node.param().stride; - const int padding_type = (node.param().padding.type == ir::PaddingType::SAME); - const auto padding = neurun::util::calculatePadding(node.param().padding, ofm_shape, ifm_shape, - stride, ker_width, ker_height); - - auto ofm_alloc = _tensor_builder->at(ofm_index); - auto ifm_alloc = _tensor_builder->at(ifm_index); - auto ker_alloc = _tensor_builder->at(ker_index); - const auto backend_layout = ofm_alloc->layout(); - assert(backend_layout == ifm_alloc->layout()); - - const auto ofm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ofm_index), _current_subg_layout, backend_layout); - const auto ifm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ifm_index), _current_subg_layout, backend_layout); - const auto ker_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ker_index), _current_subg_layout, backend_layout); - - auto fn = nnfw::cpp14::make_unique<::neurun::backend::srcn::kernel::TransposeConvLayer>(); - - fn->configure(ifm_alloc->buffer(), ifm_backend_descr, ker_alloc->buffer(), ker_backend_descr, - padding_type, padding.left, padding.right, padding.top, padding.bottom, - stride.horizontal, stride.vertical, ofm_alloc->buffer(), ofm_backend_descr, - backend_layout); - - _execution_builder->append(std::move(fn)); -} - -void KernelGenerator::visit(const ir::operation::Add &node) -{ - using ir::operation::Add; - - const auto ofm_index{node.getOutputs().at(0)}; - const auto lhs_index{node.getInputs().at(Add::Input::LHS)}; - const auto rhs_index{node.getInputs().at(Add::Input::RHS)}; - - const auto activation = node.param().activation; - - auto ofm_alloc = _tensor_builder->at(ofm_index).get(); - auto lhs_alloc = _tensor_builder->at(lhs_index).get(); - auto rhs_alloc = _tensor_builder->at(rhs_index).get(); - - const auto backend_layout = ofm_alloc->layout(); - assert(backend_layout == lhs_alloc->layout() && backend_layout == rhs_alloc->layout()); - - const auto ofm_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(ofm_index), _current_subg_layout, backend_layout); - const auto lhs_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(lhs_index), _current_subg_layout, backend_layout); - const auto rhs_backend_descr = ::neurun::backend::srcn::kernel::getTensorDescriptor( - _ctx.at(rhs_index), _current_subg_layout, backend_layout); - - auto fn = nnfw::cpp14::make_unique<::neurun::backend::srcn::kernel::AddLayer>(); - - fn->configure(lhs_alloc->buffer(), lhs_backend_descr, rhs_alloc->buffer(), rhs_backend_descr, - activation, ofm_alloc->buffer(), ofm_backend_descr, backend_layout); - - _execution_builder->append(std::move(fn)); -} - -} // namespace srcn -} // namespace backend -} // namespace neurun |