Files
FastDeploy/paddle2onnx/optimizer/replace_add_to_identity.h
Jason 6343b0db47 [Build] Support build with source code of Paddle2ONNX (#1559)
* Add notes for tensors

* Optimize some apis

* move some warnings

* Support build with Paddle2ONNX

* Add protobuf support

* Fix compile on mac

* add clearn package script

* Add paddle2onnx code

* remove submodule

* Add onnx ocde

* remove softlink

* add onnx code

* fix error

* Add cmake file

* fix patchelf

* update paddle2onnx

* Delete .gitmodules

---------

Co-authored-by: PaddleCI <paddle_ci@example.com>
Co-authored-by: pangyoki <pangyoki@126.com>
Co-authored-by: jiangjiajun <jiangjiajun@baidu.lcom>
2023-03-17 10:03:22 +08:00

123 lines
3.8 KiB
C++

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
/*
* SPDX-License-Identifier: Apache-2.0
*/
#pragma once
// Before:
// X = Constant() all elements equal to 0, shape is () or (1,)
// Y = Tensor()
// C = X + Y
// After:
// C = Identity(Y)
#include <numeric>
#include <cmath>
#include "onnx/defs/tensor_util.h"
#include "onnxoptimizer/pass.h"
namespace ONNX_NAMESPACE {
namespace optimization {
struct ReplaceAddToIdentity final : public PredicateBasedPass {
explicit ReplaceAddToIdentity()
: PredicateBasedPass(PassType::Fuse, PassEfficiency::Complete,
PassOptimizationType::Compute) {}
std::string getPassName() const override {
return "replace_add_to_identity";
}
bool patternMatchPredicate(Node* node) override {
return node->kind() == kAdd &&
(node->inputs()[0]->node()->kind() == kConstant || node->inputs()[1]->node()->kind() == kConstant);
}
bool runTransform(Node* n, Graph& graph,
NodeDestroyType& destroy_current) override {
Node* add_node = n;
Node* add_ipt_0 = n->inputs()[0]->node();
Node* add_ipt_1 = n->inputs()[1]->node();
if (add_ipt_0->kind() == kConstant) {
auto bias = add_ipt_0->t(kvalue);
if (bias.sizes().size() == 1 && bias.sizes()[0] != 1) {
return false;
}
if (bias.sizes().size() > 1) {
return false;
}
const auto& float_data = bias.floats();
if (float_data.size() > 0 && fabs(float_data[0]) > 1e-05) {
return false;
}
const auto& double_data = bias.doubles();
if (double_data.size() > 0 && fabs(double_data[0]) > 1e-05) {
return false;
}
const auto& int32_data = bias.int32s();
if (int32_data.size() > 0 && int32_data[0] != 0) {
return false;
}
const auto& int64_data = bias.int64s();
if (int64_data.size() > 0 && int64_data[0] != 0) {
return false;
}
if (float_data.size() == 0 && double_data.size() == 0 && int32_data.size() == 0 && int64_data.size() == 0) {
return false;
}
if (!tryReplacingAllUsesWith(add_node->output(), add_node->inputs()[1])) {
return false;
}
} else {
auto bias = add_ipt_1->t(kvalue);
if (bias.sizes().size() == 1 && bias.sizes()[0] != 1) {
return false;
}
if (bias.sizes().size() > 1) {
return false;
}
const auto& float_data = bias.floats();
if (float_data.size() > 0 && fabs(float_data[0]) > 1e-05) {
return false;
}
const auto& double_data = bias.doubles();
if (double_data.size() > 0 && fabs(double_data[0]) > 1e-05) {
return false;
}
const auto& int32_data = bias.int32s();
if (int32_data.size() > 0 && int32_data[0] != 0) {
return false;
}
const auto& int64_data = bias.int64s();
if (int64_data.size() > 0 && int64_data[0] != 0) {
return false;
}
if (float_data.size() == 0 && double_data.size() == 0 && int32_data.size() == 0 && int64_data.size() == 0) {
return false;
}
if (!tryReplacingAllUsesWith(add_node->output(), add_node->inputs()[0])) {
return false;
}
}
return true;
}
};
} // namespace optimization
} // namespace ONNX_NAMESPACE