!10324 [lite]add argmax、layernorm、batchmatmul for minidr
From: @xu_anyue Reviewed-by: Signed-off-by:pull/10324/MERGE
mindspore-ci-bot
4 years ago
committed by
Gitee
commit
00455b9559
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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/gelu.h"
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#include <memory>
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#include "include/errorcode.h"
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#include "src/common/log_adapter.h"
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#include "src/tensor.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 GeLU::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_GeLU;
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}
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if (this->primitive_->value.type != schema::PrimitiveType_GeLU) {
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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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this->primitive_->value.value = new (std::nothrow) schema::GeLUT();
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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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#endif
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} // namespace lite
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} // namespace mindspore
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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 LITE_MINDSPORE_LITE_C_OPS_GELU_H_
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#define LITE_MINDSPORE_LITE_C_OPS_GELU_H_
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#include <vector>
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#include <set>
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#include <cmath>
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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 GeLU : public PrimitiveC {
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public:
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GeLU() = default;
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~GeLU() = default;
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#ifdef PRIMITIVE_WRITEABLE
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MS_DECLARE_PARENT(GeLU, PrimitiveC);
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explicit GeLU(schema::PrimitiveT *primitive) : PrimitiveC(primitive) {}
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int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
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#endif
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};
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} // namespace lite
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} // namespace mindspore
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#endif // LITE_MINDSPORE_LITE_C_OPS_GELU_H_
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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 "tools/optimizer/graph/mindir_inputs_adjust_pass.h"
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#include <vector>
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#include <memory>
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#include "src/common/log_adapter.h"
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#include "src/ops/primitive_c.h"
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#include "src/tensor.h"
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using mindspore::lite::PrimitiveC;
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namespace mindspore {
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namespace opt {
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namespace {
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template <typename T>
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void CopyAttrForArgMinMax(T *left, T *right) {
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MS_ASSERT(left != null && right != nullptr);
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left->axis = right->axis;
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left->outMaxValue = right->outMaxValue;
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left->axisType = right->axisType;
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left->keepDims = right->keepDims;
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left->topK = right->topK;
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}
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} // namespace
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bool MindirInputAdjustOpPass::CheckCNodeIsArgMinMax(const CNodePtr &cnode) {
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MS_ASSERT(cnode != nullptr);
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auto prim_node = cnode->inputs().at(0);
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MS_ASSERT(prim_node != nullptr);
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auto prim_value_node = prim_node->cast<ValueNodePtr>();
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if (prim_value_node == nullptr) {
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MS_LOG(DEBUG) << "cnode first input is not valueNode.";
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return false;
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}
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auto value = prim_value_node->value();
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MS_ASSERT(value != nullptr);
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auto prim_c = value->cast<PrimitiveCPtr>();
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if (prim_c == nullptr) {
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MS_LOG(DEBUG) << "prim is not primitiveC.";
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return false;
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}
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auto prim = prim_c->primitiveT();
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MS_ASSERT(prim != nullptr);
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return prim->value.type == schema::PrimitiveType_ArgMax || prim->value.type == schema::PrimitiveType_ArgMin;
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}
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int MindirInputAdjustOpPass::AdjustArgMinMaxInputs(std::vector<AnfNodePtr> *inputs, bool index_or_value) {
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MS_ASSERT(inputs != nullptr);
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auto prim_node = inputs->at(0);
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MS_ASSERT(prim_node != nullptr);
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auto prim_value_node = prim_node->cast<ValueNodePtr>();
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if (prim_value_node == nullptr) {
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MS_LOG(ERROR) << "cnode first input is not valueNode.";
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return lite::RET_ERROR;
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}
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auto prim_value = prim_value_node->value();
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if (prim_value == nullptr) {
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MS_LOG(ERROR) << "valueNode value is nullptr.";
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return lite::RET_ERROR;
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}
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auto prim_c = prim_value->cast<PrimitiveCPtr>();
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if (prim_c == nullptr) {
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MS_LOG(ERROR) << "value is not primitiveC.";
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return lite::RET_ERROR;
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}
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auto prim = prim_c->primitiveT();
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MS_ASSERT(prim != nullptr && prim->value.value != nullptr);
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auto attr = prim->value.value;
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if (prim->value.type == schema::PrimitiveType_ArgMax) {
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reinterpret_cast<schema::ArgMaxT *>(attr)->outMaxValue = index_or_value;
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} else if (prim->value.type == schema::PrimitiveType_ArgMin) {
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reinterpret_cast<schema::ArgMinT *>(attr)->outMaxValue = index_or_value;
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}
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return lite::RET_OK;
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}
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int MindirInputAdjustOpPass::CopyPrimitiveCForArgMinMax(std::vector<AnfNodePtr> *inputs) {
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MS_ASSERT(inputs != nullptr);
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auto prim_node = inputs->at(0);
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MS_ASSERT(prim_node != nullptr);
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auto prim_value_node = prim_node->cast<ValueNodePtr>();
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if (prim_value_node == nullptr) {
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MS_LOG(ERROR) << "cnode first input is not valueNode.";
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return lite::RET_ERROR;
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}
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auto prim_value = prim_value_node->value();
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if (prim_value == nullptr) {
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MS_LOG(ERROR) << "valueNode value is nullptr.";
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return lite::RET_ERROR;
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}
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auto prim_c = prim_value->cast<PrimitiveCPtr>();
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if (prim_c == nullptr) {
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MS_LOG(ERROR) << "value is not primitiveC.";
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return lite::RET_ERROR;
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}
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auto prim = prim_c->primitiveT();
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MS_ASSERT(prim != nullptr && prim->value.value != nullptr);
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auto primitive = std::make_unique<schema::PrimitiveT>();
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if (prim->value.type == schema::PrimitiveType_ArgMax) {
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primitive->value.type = schema::PrimitiveType_ArgMax;
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auto attr = std::make_unique<schema::ArgMaxT>();
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CopyAttrForArgMinMax<schema::ArgMaxT>(attr.get(), reinterpret_cast<schema::ArgMaxT *>(prim->value.value));
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primitive->value.value = attr.release();
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} else {
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primitive->value.type = schema::PrimitiveType_ArgMin;
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auto attr = std::make_unique<schema::ArgMinT>();
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CopyAttrForArgMinMax<schema::ArgMinT>(attr.get(), reinterpret_cast<schema::ArgMinT *>(prim->value.value));
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primitive->value.value = attr.release();
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}
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auto primitive_c = PrimitiveC::Create(primitive.release());
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auto value_node = NewValueNode(std::shared_ptr<PrimitiveC>(primitive_c));
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inputs->erase(inputs->begin());
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inputs->insert(inputs->begin(), value_node);
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return lite::RET_OK;
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}
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int MindirInputAdjustOpPass::BuildCNodeForArgMinMax(const FuncGraphPtr &graph, const CNodePtr &tuple_get_item,
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const CNodePtr &argmin_max) {
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MS_ASSERT(graph != nullptr && tuple_get_item != nullptr && argmin_max != nullptr);
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auto inputs = argmin_max->inputs();
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if (CopyPrimitiveCForArgMinMax(&inputs) != lite::RET_OK) {
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MS_LOG(ERROR) << "copy argmin or argmax failed.";
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return lite::RET_ERROR;
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}
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if (AdjustArgMinMaxInputs(&inputs, false) != lite::RET_OK) {
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MS_LOG(ERROR) << "adjust argmin or argmax attr failed.";
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return lite::RET_ERROR;
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}
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auto new_cnode = graph->NewCNode(inputs);
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new_cnode->set_fullname_with_scope(argmin_max->fullname_with_scope() + "_index");
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auto type_ptr = TypeIdToType(kTypeUnknown);
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std::vector<int64_t> shape_vector;
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new_cnode->set_abstract(std::make_shared<abstract::AbstractTensor>(type_ptr, shape_vector));
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auto manager = graph->manager();
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MS_ASSERT(manager != nullptr);
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manager->Replace(tuple_get_item, new_cnode);
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return lite::RET_OK;
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}
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int MindirInputAdjustOpPass::AdjustArgMinMax(const FuncGraphPtr &graph, const CNodePtr &tuple_get_item,
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const CNodePtr &argmin_max) {
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MS_ASSERT(graph != nullptr && tuple_get_item != nullptr && argmin_max != nullptr);
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auto inputs = argmin_max->inputs();
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if (AdjustArgMinMaxInputs(&inputs, true) != lite::RET_OK) {
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MS_LOG(ERROR) << "adjust argmin or argmax attr failed.";
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return lite::RET_ERROR;
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}
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auto type_ptr = TypeIdToType(kTypeUnknown);
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std::vector<int64_t> shape_vector;
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auto abtract_tensor = std::make_shared<abstract::AbstractTensor>(type_ptr, shape_vector);
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argmin_max->set_abstract(abtract_tensor);
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auto manager = graph->manager();
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MS_ASSERT(manager != nullptr);
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manager->Replace(tuple_get_item, argmin_max);
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return lite::RET_OK;
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}
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int MindirInputAdjustOpPass::AdjustTupleGetItemWithArgMinMax(const FuncGraphPtr &graph, const CNodePtr &cnode) {
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MS_ASSERT(graph != nullptr && cnode != nullptr);
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auto inputs = cnode->inputs();
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if (inputs.size() != 3) {
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MS_LOG(ERROR) << "tupleGetItem inputs size is invalid: " << inputs.size();
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return lite::RET_ERROR;
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}
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auto argmin_max = inputs.at(1);
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MS_ASSERT(argmin_max != nullptr);
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auto argmin_max_cnode = argmin_max->cast<CNodePtr>();
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if (argmin_max_cnode == nullptr) {
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MS_LOG(ERROR) << "the second input is not a cnode.";
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return lite::RET_ERROR;
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}
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if (!CheckCNodeIsArgMinMax(argmin_max_cnode)) {
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MS_LOG(DEBUG) << "tuple_get_item first input is not argmin and argmax.";
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return lite::RET_OK;
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}
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auto index_vnode = inputs.at(2);
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auto value_node = index_vnode->cast<ValueNodePtr>();
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if (value_node == nullptr) {
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MS_LOG(ERROR) << "TupleGetItem's input 2 is not valuenode";
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return lite::RET_ERROR;
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}
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int index = lite::CastToInt(value_node->value()).front();
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if (index == 0) {
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if (BuildCNodeForArgMinMax(graph, cnode, argmin_max_cnode) != lite::RET_OK) {
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MS_LOG(ERROR) << "build new cnode failed.";
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return lite::RET_ERROR;
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}
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} else if (index == 1) {
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if (AdjustArgMinMax(graph, cnode, argmin_max_cnode) != lite::RET_OK) {
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MS_LOG(ERROR) << "adjust argmin_max failed.";
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return lite::RET_ERROR;
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}
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}
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return lite::RET_OK;
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}
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bool MindirInputAdjustOpPass::Run(const FuncGraphPtr &graph) {
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MS_ASSERT(graph != nullptr);
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auto manager = Manage(graph, true);
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if (manager == nullptr) {
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MS_LOG(ERROR) << "manager is nullptr.";
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return lite::RET_NULL_PTR;
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}
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auto node_list = TopoSort(graph->get_return());
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int status = lite::RET_OK;
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for (auto &node : node_list) {
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auto cnode = node->cast<CNodePtr>();
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if (cnode == nullptr) {
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MS_LOG(DEBUG) << "node is not cnode.";
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continue;
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}
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auto type = opt::GetCNodeType(node);
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if (type == schema::PrimitiveType_TupleGetItem) {
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status = AdjustTupleGetItemWithArgMinMax(graph, cnode);
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}
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if (status != lite::RET_OK && status != lite::RET_NO_CHANGE) {
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MS_LOG(ERROR) << "adjust input pass is failed.";
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return false;
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}
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}
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return true;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,41 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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||||||
|
*
|
||||||
|
* 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.
|
||||||
|
*/
|
||||||
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|
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#ifndef MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_MINDIR_INPUTS_ADJUST_PASS_H_
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#define MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_MINDIR_INPUTS_ADJUST_PASS_H_
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#include <string>
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#include <vector>
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#include "backend/optimizer/common/pass.h"
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#include "tools/converter/converter_flags.h"
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#include "tools/optimizer/common/gllo_utils.h"
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#include "src/param_value_lite.h"
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namespace mindspore::opt {
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class MindirInputAdjustOpPass : public Pass {
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public:
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MindirInputAdjustOpPass() : Pass("mindir_inputs_adjust_pass") {}
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~MindirInputAdjustOpPass() override = default;
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bool CheckCNodeIsArgMinMax(const CNodePtr &cnode);
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int AdjustArgMinMaxInputs(std::vector<AnfNodePtr> *inputs, bool index_or_value);
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int CopyPrimitiveCForArgMinMax(std::vector<AnfNodePtr> *inputs);
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int BuildCNodeForArgMinMax(const FuncGraphPtr &graph, const CNodePtr &tuple_get_item, const CNodePtr &argmin_max);
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int AdjustArgMinMax(const FuncGraphPtr &graph, const CNodePtr &tuple_get_item, const CNodePtr &argmin_max);
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int AdjustTupleGetItemWithArgMinMax(const FuncGraphPtr &graph, const CNodePtr &cnode);
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bool Run(const FuncGraphPtr &graph) override;
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|
};
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} // namespace mindspore::opt
|
||||||
|
#endif // MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_MINDIR_INPUTS_ADJUST_PASS_H_
|
||||||
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Reference in new issue