mindspore-ci-bot
4 years ago
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Gitee
commit
b3d43aa616
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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_NNACL_FP32_GRAD_OPTIMIZER_H_
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#define MINDSPORE_LITE_NNACL_FP32_GRAD_OPTIMIZER_H_
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#include "nnacl/op_base.h"
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typedef struct ApplyMomentumParameter {
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OpParameter op_parameter_;
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bool use_locking_;
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bool use_nesterov_;
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float grad_scale_;
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} ApplyMomentumParameter;
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typedef struct SgdParameter {
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OpParameter op_parameter_;
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float dampening_;
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bool use_nesterov_;
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float weight_decay_;
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} SgdParameter;
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#endif // MINDSPORE_LITE_NNACL_FP32_GRAD_OPTIMIZER_H_
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@ -0,0 +1,97 @@
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/**
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* Copyright 2019-2020 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/ops/sgd.h"
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namespace mindspore {
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namespace lite {
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#ifdef PRIMITIVE_WRITEABLE
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float Sgd::GetWeightDecay() const { return this->primitive_->value.AsSgd()->weightDecay; }
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float Sgd::GetDampening() const { return this->primitive_->value.AsSgd()->dampening; }
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bool Sgd::GetUseNesterov() const { return this->primitive_->value.AsSgd()->useNesterov; }
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int Sgd::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
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if (this->primitive_ == nullptr) {
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this->primitive_ = new (std::nothrow) schema::PrimitiveT;
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if (this->primitive_ == nullptr) {
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MS_LOG(ERROR) << "new primitiveT failed";
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return RET_ERROR;
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}
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this->primitive_->value.type = schema::PrimitiveType_Sgd;
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}
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if (this->primitive_->value.type != schema::PrimitiveType_Sgd) {
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MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
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return RET_ERROR;
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}
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if (this->primitive_->value.value == nullptr) {
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auto attr = std::make_unique<schema::SgdT>();
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if (attr == nullptr) {
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MS_LOG(ERROR) << "new primitiveT value failed";
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return RET_ERROR;
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}
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attr->weightDecay = GetValue<float>(prim.GetAttr("weight_decay"));
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attr->dampening = GetValue<float>(prim.GetAttr("dampening"));
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attr->useNesterov = GetValue<bool>(prim.GetAttr("nesterov"));
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this->primitive_->value.value = attr.release();
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if (this->primitive_->value.value == nullptr) {
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MS_LOG(ERROR) << "new primitiveT value failed";
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return RET_ERROR;
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}
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}
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return RET_OK;
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}
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#else
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float Sgd::GetWeightDecay() const { return this->primitive_->value_as_Sgd()->weightDecay(); }
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float Sgd::GetDampening() const { return this->primitive_->value_as_Sgd()->dampening(); }
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bool Sgd::GetUseNesterov() const { return this->primitive_->value_as_Sgd()->useNesterov(); }
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int Sgd::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
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MS_ASSERT(nullptr != primitive);
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MS_ASSERT(nullptr != fbb);
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auto attr = primitive->value_as_Sgd();
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if (attr == nullptr) {
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MS_LOG(ERROR) << "value_as_Sgd return nullptr";
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return RET_ERROR;
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}
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auto val_offset = schema::CreateSgd(*fbb, attr->weightDecay(), attr->dampening(), attr->useNesterov());
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auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_Sgd, val_offset.o);
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fbb->Finish(prim_offset);
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return RET_OK;
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}
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#endif
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int Sgd::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lite::Tensor *> outputs) {
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if (6 != inputs.size()) {
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MS_LOG(ERROR) << "Sgd should have at least 6 input tensors";
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return RET_ERROR;
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}
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if (inputs[0]->ElementsNum() != inputs[1]->ElementsNum() || inputs[0]->ElementsNum() != inputs[3]->ElementsNum() ||
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inputs[2]->ElementsNum() != 1 || inputs[4]->ElementsNum() != 1) {
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MS_LOG(ERROR) << "error input data size!";
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return RET_ERROR;
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}
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if (!outputs.empty()) {
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auto *out = outputs.front();
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MS_ASSERT(out != nullptr);
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out->set_data_type(inputs[0]->data_type());
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out->SetFormat(inputs[0]->GetFormat());
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out->set_shape({1});
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}
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return RET_OK;
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}
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} // namespace lite
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} // namespace mindspore
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