chenjianping
5 years ago
parent
6f7678f610
commit
5a83d3a7df
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "src/runtime/kernel/arm/base/caffeprelu_base.h"
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#include <vector>
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#include "schema/model_generated.h"
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#include "src/kernel_registry.h"
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#include "include/errorcode.h"
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#include "include/context.h"
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using mindspore::lite::KernelRegistrar;
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using mindspore::lite::RET_ERROR;
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using mindspore::lite::RET_OK;
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using mindspore::schema::PrimitiveType_CaffePReLU;
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namespace mindspore::kernel {
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int CaffePreluBaseCPUKernel::Init() { return RET_OK; }
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kernel::LiteKernel *CpuCaffePreluFp32KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
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const std::vector<lite::tensor::Tensor *> &outputs,
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OpParameter *opParameter, const Context *ctx,
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const kernel::KernelKey &desc,
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const mindspore::lite::PrimitiveC *primitive) {
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if (opParameter == nullptr) {
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MS_LOG(ERROR) << "Input opParameter is nullptr!";
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return nullptr;
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}
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MS_ASSERT(desc.type == schema::PrimitiveType_CaffePrelu);
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auto *kernel = new (std::nothrow) CaffePreluBaseCPUKernel(opParameter, inputs, outputs, ctx, primitive);
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if (kernel == nullptr) {
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MS_LOG(ERROR) << "new PreluCPUKernel fail!";
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return nullptr;
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}
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auto ret = kernel->Init();
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if (ret != RET_OK) {
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delete kernel;
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MS_LOG(ERROR) << "Init kernel failed, name: " << opParameter->name_ << ", type: "
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<< schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(opParameter->type_));
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return nullptr;
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}
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return kernel;
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}
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REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_CaffePReLU, CpuCaffePreluFp32KernelCreator)
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} // namespace mindspore::kernel
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@ -1,52 +0,0 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_CAFFEPRELU_BASE_H_
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#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_CAFFEPRELU_BASE_H_
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#include <vector>
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#include "src/lite_kernel.h"
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#include "src/runtime/kernel/arm/nnacl/caffeprelu_parameter.h"
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#include "src/runtime/kernel/arm/base/layout_transform.h"
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using mindspore::lite::Context;
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namespace mindspore::kernel {
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class CaffePreluBaseCPUKernel : public LiteKernel {
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public:
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CaffePreluBaseCPUKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs,
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const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
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const mindspore::lite::PrimitiveC *primitive)
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: LiteKernel(parameter, inputs, outputs, ctx, primitive), ctx_(ctx), thread_count_(ctx->thread_num_) {
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prelu_param_ = reinterpret_cast<CaffePreluParameter *>(parameter);
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}
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~CaffePreluBaseCPUKernel() = default;
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int Init() override;
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int ReSize() override { return 0; }
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int Run() override { return 0; }
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protected:
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const Context *ctx_;
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int thread_count_;
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CaffePreluParameter *prelu_param_;
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};
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} // namespace mindspore::kernel
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#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_CAFFEPRELU_BASE_H_
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@ -1,98 +0,0 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "src/runtime/kernel/arm/fp32/caffeprelu.h"
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#include <vector>
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#include "schema/model_generated.h"
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#include "src/runtime/kernel/arm/nnacl/caffeprelu.h"
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#include "src/kernel_registry.h"
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#include "include/errorcode.h"
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#include "src/runtime/runtime_api.h"
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using mindspore::kernel::KERNEL_ARCH::kCPU;
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using mindspore::lite::KernelRegistrar;
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using mindspore::lite::RET_ERROR;
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using mindspore::lite::RET_OK;
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using mindspore::schema::PrimitiveType_CaffePReLU;
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namespace mindspore::kernel {
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int CaffePReluCPUKernel::Init() { return RET_OK; }
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int CaffePReluCPUKernel::DoExcute(int task_id) {
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CaffePRelu(input_data, output_data, prelu_param_, task_id);
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return RET_OK;
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}
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int CaffePReluRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
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auto PReludata = reinterpret_cast<CaffePReluCPUKernel *>(cdata);
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auto ret = PReludata->DoExcute(task_id);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "PReluRun error task_id[" << task_id << "] error_code[" << ret << "]";
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return RET_ERROR;
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}
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return RET_OK;
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}
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int CaffePReluCPUKernel::Run() {
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auto prepare_ret = Prepare();
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if (prepare_ret != RET_OK) {
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MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
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return prepare_ret;
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}
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auto input = in_tensors_[0];
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auto input1 = in_tensors_[1];
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prelu_param_->input_num_ = input->ElementsNum();
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input_data = reinterpret_cast<float *>(input->Data());
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output_data = reinterpret_cast<float *>(out_tensors_[0]->Data());
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auto channels = input->shape();
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prelu_param_->negtive_slope_ = reinterpret_cast<float *>(input1->Data());
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prelu_param_->channel_num_ = channels.at(channels.size() - 1);
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auto ret = LiteBackendParallelLaunch(CaffePReluRun, this, prelu_param_->op_parameter_.thread_num_);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "PReluDwRun error: error_code[" << ret << "]";
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return RET_ERROR;
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}
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return RET_OK;
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}
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kernel::LiteKernel *CpuCaffePReluFp32KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
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const std::vector<lite::tensor::Tensor *> &outputs,
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OpParameter *opParameter, const lite::Context *ctx,
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const kernel::KernelKey &desc,
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const mindspore::lite::PrimitiveC *primitive) {
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if (opParameter == nullptr) {
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MS_LOG(ERROR) << "input opParameter is nullptr!";
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return nullptr;
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}
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MS_ASSERT(desc.type == schema::PrimitiveType_Prelu);
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auto *kernel = new (std::nothrow) CaffePReluCPUKernel(opParameter, inputs, outputs, ctx, primitive);
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if (kernel == nullptr) {
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MS_LOG(ERROR) << "new PReluCPUKernel fail!";
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return nullptr;
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}
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auto ret = kernel->Init();
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "Init kernel failed, name: " << opParameter->name_ << ", type: "
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<< schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(opParameter->type_));
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delete kernel;
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return nullptr;
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}
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return kernel;
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}
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REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_CaffePReLU, CpuCaffePReluFp32KernelCreator)
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} // namespace mindspore::kernel
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@ -0,0 +1,104 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "src/runtime/kernel/arm/fp32/leaky_relu.h"
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#include <vector>
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#include "schema/model_generated.h"
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#include "src/runtime/kernel/arm/nnacl/fp32/leaky_relu.h"
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#include "src/kernel_registry.h"
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#include "include/errorcode.h"
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#include "src/runtime/runtime_api.h"
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using mindspore::kernel::KERNEL_ARCH::kCPU;
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using mindspore::lite::KernelRegistrar;
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using mindspore::lite::RET_ERROR;
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using mindspore::lite::RET_OK;
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using mindspore::schema::PrimitiveType_LeakyReLU;
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using mindspore::schema::PrimitiveType_Prelu;
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namespace mindspore::kernel {
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namespace {
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int LeakyReluRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
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auto kernel_relu = reinterpret_cast<LeakyReluCPUKernel *>(cdata);
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auto ret = kernel_relu->DoExcute(task_id);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "LeakyReluRun error task_id[" << task_id << "] error_code[" << ret << "]";
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return RET_ERROR;
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}
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return RET_OK;
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}
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} // namespace
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LeakyReluCPUKernel::~LeakyReluCPUKernel() {
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if (prelu_param_->slope_ != nullptr) {
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free(prelu_param_->slope_);
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prelu_param_->slope_ = nullptr;
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}
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}
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int LeakyReluCPUKernel::Init() { return RET_OK; }
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int LeakyReluCPUKernel::DoExcute(int task_id) {
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DoLeakyRelu(input_data, output_data, prelu_param_, task_id);
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return RET_OK;
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}
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int LeakyReluCPUKernel::Run() {
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auto prepare_ret = Prepare();
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if (prepare_ret != RET_OK) {
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MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
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return prepare_ret;
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}
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auto input = in_tensors_.at(0);
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prelu_param_->input_num_ = input->ElementsNum();
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input_data = reinterpret_cast<float *>(input->Data());
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output_data = reinterpret_cast<float *>(out_tensors_.at(0)->Data());
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auto ret = LiteBackendParallelLaunch(LeakyReluRun, this, context_->thread_num_);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "PReluDwRun error: error_code[" << ret << "]";
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return RET_ERROR;
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}
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return RET_OK;
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}
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kernel::LiteKernel *CpuLeakyReluFp32KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
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const std::vector<lite::tensor::Tensor *> &outputs,
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OpParameter *param, const lite::Context *ctx,
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const kernel::KernelKey &desc,
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const mindspore::lite::PrimitiveC *primitive) {
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if (param == nullptr) {
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MS_LOG(ERROR) << "input param is nullptr!";
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return nullptr;
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}
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MS_ASSERT(desc.type == schema::PrimitiveType_LeakyRelu);
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auto *kernel = new (std::nothrow) LeakyReluCPUKernel(param, inputs, outputs, ctx, primitive);
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if (kernel == nullptr) {
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MS_LOG(ERROR) << "new LeakyReluCPUKernel fail!";
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return nullptr;
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}
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auto ret = kernel->Init();
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "Init kernel failed, name: " << param->name_ << ", type: "
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<< schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(param->type_));
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delete kernel;
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return nullptr;
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}
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return kernel;
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}
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REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_LeakyReLU, CpuLeakyReluFp32KernelCreator)
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REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_Prelu, CpuLeakyReluFp32KernelCreator)
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} // namespace mindspore::kernel
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@ -1,35 +0,0 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_CAFFEPRELU_PARAMETER_H_
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#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_CAFFEPRELU_PARAMETER_H_
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#include "src/runtime/kernel/arm/nnacl/op_base.h"
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#define CAFFEPRELU_OFFSET_MAX_SIZE 4
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struct CaffePreluParameter {
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OpParameter op_parameter_;
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bool channelShared;
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double alpha_;
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int64_t offset_[CAFFEPRELU_OFFSET_MAX_SIZE];
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int64_t in_offset_[CAFFEPRELU_OFFSET_MAX_SIZE];
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int64_t axis_;
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const int *in_shape_;
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const int *out_shape_;
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int input_dim_;
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};
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#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_CAFFEPRELU_PARAMETER_H_
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||||||
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