yoni
4 years ago
committed by
Haim Moushkatel
parent
3b46781aa0
commit
15d4f6fb04
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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/sparse_softmax_cross_entropy.h"
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#ifndef PRIMITIVE_WRITEABLE
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#include "src/ops/ops_register.h"
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#endif
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namespace mindspore {
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namespace lite {
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#ifdef PRIMITIVE_WRITEABLE
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int SparseSoftmaxCrossEntropy::GetIsGrad() const {
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return this->primitive_->value.AsSparseSoftmaxCrossEntropy()->isGrad;
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}
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void SparseSoftmaxCrossEntropy::SetIsGrad(int isGrad) {
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this->primitive_->value.AsSparseSoftmaxCrossEntropy()->isGrad = isGrad;
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}
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int SparseSoftmaxCrossEntropy::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_SparseSoftmaxCrossEntropy;
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}
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if (this->primitive_->value.type != schema::PrimitiveType_SparseSoftmaxCrossEntropy) {
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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 = new (std::nothrow) schema::SparseSoftmaxCrossEntropyT();
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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->isGrad = GetValue<bool>(prim.GetAttr("is_grad"));
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this->primitive_->value.value = attr;
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if (this->primitive_->value.value == nullptr) {
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MS_LOG(ERROR) << "primitive value is nullptr";
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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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int SparseSoftmaxCrossEntropy::GetIsGrad() const {
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return this->primitive_->value_as_SparseSoftmaxCrossEntropy()->isGrad();
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}
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int SparseSoftmaxCrossEntropy::UnPackToFlatBuilder(const schema::Primitive *primitive,
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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_SparseSoftmaxCrossEntropy();
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if (attr == nullptr) {
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MS_LOG(ERROR) << "value_as_SparseSoftmaxCrossEntropy return nullptr";
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return RET_ERROR;
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}
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auto val_offset = schema::CreateSparseSoftmaxCrossEntropy(*fbb, attr->isGrad());
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auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_SparseSoftmaxCrossEntropy, 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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PrimitiveC *SparseSoftmaxCrossEntropyCreator(const schema::Primitive *primitive) {
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return PrimitiveC::NewPrimitiveC<SparseSoftmaxCrossEntropy>(primitive);
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}
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Registry SparseSoftmaxCrossEntropyRegistry(schema::PrimitiveType_SparseSoftmaxCrossEntropy,
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SparseSoftmaxCrossEntropyCreator);
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#endif
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int SparseSoftmaxCrossEntropy::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outputs) {
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if (2 != inputs.size()) {
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MS_LOG(ERROR) << "SparseSoftmaxCrossEntropy should have at two inputs";
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return RET_ERROR;
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}
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if (1 != outputs.size()) {
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MS_LOG(ERROR) << "SparseSoftmaxCrossEntropy should have one output";
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return RET_ERROR;
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}
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auto *in0 = inputs.front();
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MS_ASSERT(in0 != nullptr);
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auto *out = outputs.front();
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MS_ASSERT(out != nullptr);
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if (GetIsGrad() != 0) {
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out->set_shape(in0->shape());
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out->set_data_type(in0->data_type());
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out->set_format(in0->format());
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} else {
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std::vector<int> outshape;
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outshape.push_back(1);
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out->set_shape(outshape);
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out->set_data_type(in0->data_type());
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out->set_format(in0->format());
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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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@ -0,0 +1,48 @@
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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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#ifndef MINDSPORE_LITE_SRC_OPS_SPARSE_SOFTMAX_CROSS_ENTROPY_H_
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#define MINDSPORE_LITE_SRC_OPS_SPARSE_SOFTMAX_CROSS_ENTROPY_H_
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#include <vector>
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#include <set>
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#include <cmath>
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#include <memory>
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#include "src/ops/primitive_c.h"
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namespace mindspore {
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namespace lite {
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class SparseSoftmaxCrossEntropy : public PrimitiveC {
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public:
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SparseSoftmaxCrossEntropy() = default;
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~SparseSoftmaxCrossEntropy() = default;
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#ifdef PRIMITIVE_WRITEABLE
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MS_DECLARE_PARENT(SparseSoftmaxCrossEntropy, PrimitiveC);
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explicit SparseSoftmaxCrossEntropy(schema::PrimitiveT *primitive) : PrimitiveC(primitive) {}
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void SetIsGrad(int isGrad);
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int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
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#else
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int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
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#endif
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int InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Tensor *> outputs_) override;
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int GetIsGrad() const;
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};
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} // namespace lite
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} // namespace mindspore
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#endif // MINDSPORE_LITE_SRC_OPS_SPARSE_SOFTMAX_CROSS_ENTROPY_H_
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