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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>
83 lines
2.8 KiB
C++
83 lines
2.8 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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#include "paddle2onnx/mapper/nn/conv3d.h"
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#include <string>
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#include <vector>
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namespace paddle2onnx {
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REGISTER_MAPPER(conv3d, Conv3dMapper)
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int32_t Conv3dMapper::GetMinOpset(bool verbose) {
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// NDHWC is not supported
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if (data_format_ == "NDHWC") {
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Error() << "Cannot support input with NDHWC format." << std::endl;
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return -1;
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}
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if (padding_algorithm_ == "EXPLICIT") {
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if (paddings_.size() != 3 && paddings_.size() != 6) {
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Error() << "While padding_algorithm is EXPLICIT, size of paddings should "
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"be 3 or 6."
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<< std::endl;
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return -1;
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}
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}
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if (dilations_[0] != 1 || dilations_[1] != 1 || dilations_[2] != 1) {
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if (padding_algorithm_ == "SAME") {
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Error() << "While dilations != 1, cannot support padding = 'SAME'."
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<< std::endl;
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return -1;
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}
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}
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return 7;
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}
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void Conv3dMapper::Opset7() {
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auto kernel_info = GetInput("Filter");
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auto input_info = GetInput("Input");
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auto output_info = GetOutput("Output");
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auto node = helper_->MakeNode(
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"Conv", {input_info[0].name, kernel_info[0].name}, {output_info[0].name});
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AddAttribute(node, "dilations", dilations_);
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std::vector<int64_t> kernel_shape = {kernel_info[0].shape[2],
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kernel_info[0].shape[3],
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kernel_info[0].shape[4]};
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AddAttribute(node, "kernel_shape", kernel_shape);
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AddAttribute(node, "strides", strides_);
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AddAttribute(node, "group", groups_);
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if (padding_algorithm_ == "SAME") {
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std::string auto_pad = "SAME_UPPER";
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AddAttribute(node, "auto_pad", auto_pad);
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} else if (padding_algorithm_ == "VALID") {
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std::string auto_pad = "VALID";
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AddAttribute(node, "auto_pad", auto_pad);
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} else {
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std::vector<int64_t> paddings;
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if (paddings_.size() == 3) {
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paddings.insert(paddings.begin(), paddings_.begin(), paddings_.end());
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paddings.insert(paddings.begin(), paddings_.begin(), paddings_.end());
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} else {
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std::vector<int64_t> index = {0, 2, 4, 1, 3, 5};
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for (auto &i : index) {
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paddings.push_back(paddings_[i]);
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}
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}
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AddAttribute(node, "pads", paddings);
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}
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}
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} // namespace paddle2onnx
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