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https://github.com/PaddlePaddle/FastDeploy.git
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6343b0db47
* 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>
123 lines
3.8 KiB
C++
123 lines
3.8 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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* SPDX-License-Identifier: Apache-2.0
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*/
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#pragma once
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// Before:
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// X = Constant() all elements equal to 1, shape is () or (1,)
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// Y = Tensor()
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// C = X * Y
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// After:
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// C = Identity(Y)
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#include <numeric>
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#include <cmath>
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#include "onnx/defs/tensor_util.h"
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#include "onnxoptimizer/pass.h"
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namespace ONNX_NAMESPACE {
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namespace optimization {
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struct ReplaceMulToIdentity final : public PredicateBasedPass {
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explicit ReplaceMulToIdentity()
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: PredicateBasedPass(PassType::Fuse, PassEfficiency::Complete,
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PassOptimizationType::Compute) {}
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std::string getPassName() const override {
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return "replace_mul_to_identity";
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}
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bool patternMatchPredicate(Node* node) override {
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return node->kind() == kMul &&
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(node->inputs()[0]->node()->kind() == kConstant || node->inputs()[1]->node()->kind() == kConstant);
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}
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bool runTransform(Node* n, Graph& graph,
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NodeDestroyType& destroy_current) override {
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Node* mul_node = n;
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Node* mul_ipt_0 = n->inputs()[0]->node();
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Node* mul_ipt_1 = n->inputs()[1]->node();
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if (mul_ipt_0->kind() == kConstant) {
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auto scale = mul_ipt_0->t(kvalue);
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if (scale.sizes().size() == 1 && scale.sizes()[0] != 1) {
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return false;
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}
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if (scale.sizes().size() > 1) {
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return false;
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}
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const auto& float_data = scale.floats();
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if (float_data.size() > 0 && fabs(float_data[0] - 1.0) > 1e-05) {
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return false;
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}
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const auto& double_data = scale.doubles();
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if (double_data.size() > 0 && fabs(double_data[0] - 1.0) > 1e-05) {
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return false;
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}
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const auto& int32_data = scale.int32s();
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if (int32_data.size() > 0 && int32_data[0] != 1) {
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return false;
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}
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const auto& int64_data = scale.int64s();
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if (int64_data.size() > 0 && int64_data[0] != 1) {
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return false;
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}
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if (float_data.size() == 0 && double_data.size() == 0 && int32_data.size() == 0 && int64_data.size() == 0) {
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return false;
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}
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if (!tryReplacingAllUsesWith(mul_node->output(), mul_node->inputs()[1])) {
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return false;
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}
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} else {
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auto scale = mul_ipt_1->t(kvalue);
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if (scale.sizes().size() == 1 && scale.sizes()[0] != 1) {
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return false;
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}
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if (scale.sizes().size() > 1) {
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return false;
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}
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const auto& float_data = scale.floats();
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if (float_data.size() > 0 && fabs(float_data[0] - 1.0) > 1e-05) {
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return false;
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}
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const auto& double_data = scale.doubles();
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if (double_data.size() > 0 && fabs(double_data[0] - 1.0) > 1e-05) {
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return false;
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}
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const auto& int32_data = scale.int32s();
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if (int32_data.size() > 0 && int32_data[0] != 1) {
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return false;
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}
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const auto& int64_data = scale.int64s();
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if (int64_data.size() > 0 && int64_data[0] != 1) {
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return false;
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}
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if (float_data.size() == 0 && double_data.size() == 0 && int32_data.size() == 0 && int64_data.size() == 0) {
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return false;
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}
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if (!tryReplacingAllUsesWith(mul_node->output(), mul_node->inputs()[0])) {
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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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};
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} // namespace optimization
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} // namespace ONNX_NAMESPACE
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