lzk
4 years ago
parent
15024df14b
commit
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/**
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* Copyright 2021 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 <vector>
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#include "include/errorcode.h"
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#include "schema/model_generated.h"
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#include "src/runtime/kernel/arm/fp16/bias_fp16.h"
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#include "src/kernel_registry.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_NULL_PTR;
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using mindspore::lite::RET_OK;
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using mindspore::schema::PrimitiveType_BiasAdd;
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namespace mindspore::kernel {
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int BiasCPUFp16Kernel::ReSize() {
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auto dims = in_tensors_.at(0)->shape();
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bias_param_->ndim_ = dims.size();
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if (bias_param_->ndim_ < 1 || bias_param_->ndim_ > 5) {
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MS_LOG(ERROR) << "input shape is invalid";
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return RET_ERROR;
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}
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for (size_t i = 0; i < bias_param_->ndim_; i++) {
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bias_param_->in_shape0_[i] = dims[i];
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bias_param_->in_shape1_[i] = 1;
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bias_param_->out_shape_[i] = dims[i];
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}
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bias_param_->in_shape1_[bias_param_->ndim_ - 1] = dims[bias_param_->ndim_ - 1];
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return RET_OK;
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}
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int BiasCPUFp16Kernel::Run() {
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auto in = reinterpret_cast<float16_t *>(in_tensors_.at(0)->MutableData());
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auto out = reinterpret_cast<float16_t *>(out_tensors_.at(0)->MutableData());
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size_t data_size = in_tensors_.at(0)->ElementsNum();
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MS_ASSERT(context_->allocator != nullptr);
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auto *tile_in = reinterpret_cast<float16_t *>(context_->allocator->Malloc(data_size * sizeof(float16_t)));
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auto *tile_bias = reinterpret_cast<float16_t *>(context_->allocator->Malloc(data_size * sizeof(float16_t)));
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if (tile_in == nullptr || tile_bias == nullptr) {
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MS_LOG(ERROR) << "Memory allocation failed";
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context_->allocator->Free(tile_in);
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context_->allocator->Free(tile_bias);
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return RET_NULL_PTR;
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}
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BroadcastAddFp16(in, bias_data_, tile_in, tile_bias, out, data_size, bias_param_);
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context_->allocator->Free(tile_in);
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context_->allocator->Free(tile_bias);
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return RET_OK;
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}
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BiasCPUFp16Kernel::~BiasCPUFp16Kernel() {
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if ((bias_data_type_ == kNumberTypeFloat || bias_data_type_ == kNumberTypeFloat32) && bias_data_ != nullptr) {
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free(bias_data_);
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bias_data_ = nullptr;
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}
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}
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int BiasCPUFp16Kernel::Init() {
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auto bias_tensor = in_tensors_.at(1);
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MS_ASSERT(bias_tensor != nullptr);
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bias_data_type_ = bias_tensor->data_type();
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if (bias_data_type_ == kNumberTypeFloat || bias_data_type_ == kNumberTypeFloat32) {
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bias_data_ = reinterpret_cast<float16_t *>(malloc(bias_tensor->ElementsNum() * sizeof(float16_t)));
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if (bias_data_ == nullptr) {
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MS_LOG(ERROR) << "bias_data_ is nullptr";
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return RET_NULL_PTR;
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}
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auto *bias = reinterpret_cast<float *>(bias_tensor->MutableData());
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if (bias != nullptr) {
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MS_LOG(ERROR) << "bias is nullptr!";
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return RET_NULL_PTR;
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}
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for (int i = 0; i < bias_tensor->ElementsNum(); ++i) {
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bias_data_[i] = (float16_t)(bias[i]);
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}
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} else {
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bias_data_ = reinterpret_cast<float16_t *>(bias_tensor->MutableData());
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if (bias_data_ == nullptr) {
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MS_LOG(ERROR) << "bias_data_ is nullptr";
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return RET_NULL_PTR;
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}
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}
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if (!InferShapeDone()) {
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return RET_OK;
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}
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return ReSize();
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}
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REG_KERNEL(kCPU, kNumberTypeFloat16, PrimitiveType_BiasAdd, LiteKernelCreator<BiasCPUFp16Kernel>)
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} // namespace mindspore::kernel
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@ -0,0 +1,45 @@
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/**
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* Copyright 2021 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_FP16_BIAS_H_
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#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP16_BIAS_H_
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#include <vector>
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#include "src/lite_kernel.h"
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#include "nnacl/fp16/arithmetic_fp16.h"
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namespace mindspore::kernel {
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class BiasCPUFp16Kernel : public LiteKernel {
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public:
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BiasCPUFp16Kernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
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const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
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const mindspore::lite::PrimitiveC *primitive)
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: LiteKernel(parameter, inputs, outputs, ctx, primitive) {
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bias_param_ = reinterpret_cast<ArithmeticParameter *>(parameter);
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}
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~BiasCPUFp16Kernel() override;
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int Init() override;
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int ReSize() override;
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int Run() override;
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private:
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ArithmeticParameter *bias_param_ = nullptr;
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float16_t *bias_data_ = nullptr;
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TypeId bias_data_type_;
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};
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} // namespace mindspore::kernel
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#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP16_BIAS_H_
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