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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>
97 lines
3.0 KiB
C++
97 lines
3.0 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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// Only support conv2d + bias now
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#include <numeric>
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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 FusePaddleConvBias final : public PredicateBasedPass {
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explicit FusePaddleConvBias()
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: PredicateBasedPass(PassType::Fuse, PassEfficiency::Complete,
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PassOptimizationType::Compute) {}
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std::string getPassName() const override { return "fuse_paddle_conv_bias"; }
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bool patternMatchPredicate(Node* node) override {
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return node->kind() == kAdd && node->inputs()[0]->node()->kind() == kConv &&
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node->inputs()[1]->node()->kind() == kConstant &&
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node->inputs()[0]->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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destroy_current = NodeDestroyType::DestroyZero;
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// check if Conv is only used by Add
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if (n->inputs()[0]->uses().size() > 1) {
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return false;
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}
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// check if bias is only used by Add
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if (n->inputs()[1]->uses().size() > 1) {
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return false;
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}
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Node* add = n;
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Node* conv = n->inputs()[0]->node();
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Node* bias = n->inputs()[1]->node();
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Node* weight = conv->inputs()[1]->node();
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if (conv->inputs().size() > 2) {
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return false;
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}
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Tensor bias_tensor = bias->t(kvalue);
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Tensor weight_tensor = weight->t(kvalue);
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const auto& bias_shape = bias_tensor.sizes();
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const auto& weight_shape = weight_tensor.sizes();
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if (bias_shape.size() != 4 || bias_shape.size() != weight_shape.size()) {
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return false;
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}
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if (bias_shape[0] != 1 || bias_shape[2] != 1 || bias_shape[3] != 1) {
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return false;
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}
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if (bias_shape[1] != weight_shape[0]) {
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return false;
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}
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// reshape bias node
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bias_tensor.sizes().clear();
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bias_tensor.sizes().push_back(weight_shape[0]);
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bias->t_(kvalue, std::move(bias_tensor));
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conv->addInput(bias->outputs()[0]);
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conv->output()->setSizes(add->output()->sizes());
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conv->output()->setElemType(add->output()->elemType());
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const bool replacing_success =
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tryReplacingAllUsesWith(add->output(), add->inputs()[0]);
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if (!replacing_success) {
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return false;
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}
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destroy_current = NodeDestroyType::DestroyOne;
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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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