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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>
88 lines
3.1 KiB
C++
Executable File
88 lines
3.1 KiB
C++
Executable File
// 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/quantize/quantize_linear.h"
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namespace paddle2onnx {
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REGISTER_MAPPER(quantize_linear, QuantizeLinearMapper)
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int32_t QuantizeLinearMapper::GetMinOpset(bool verbose) {
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if (!IsConstantInput("Scale")) {
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Error() << "Input `Scale` requires to be a constant tensor." << std::endl;
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return -1;
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}
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std::vector<float> scales;
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if (!TryGetInputValue("Scale", &scales)) {
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Error() << "Failed to read tensor value of `Scale`." << std::endl;
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return -1;
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}
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if (bit_length_ != 8) {
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Error() << "Only support bit_length = 8." << std::endl;
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return -1;
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}
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if (round_type_ != 0) {
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Error() << "The round_type attr of quantize_linear must be 0." << std::endl;
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return -1;
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}
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if (scales.size() > 1) {
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auto x_info = GetInput("X");
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if (x_info[0].shape[quant_axis_] != scales.size()) {
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Error() << "Scale size must equal to the size of input quantize axis."
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<< std::endl;
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return -1;
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}
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Logger(verbose, 13) << "While size of scales greater than 1, "
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<< RequireOpset(13) << std::endl;
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return 13;
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}
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Logger(verbose, 10) << RequireOpset(10) << std::endl;
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return 10;
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}
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void QuantizeLinearMapper::Opset10() {
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auto x_info = GetInput("X");
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std::vector<float> scales;
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Assert(TryGetInputValue("Scale", &scales),
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"Failed to read tensor value of `Scale`.");
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std::vector<float> onnx_scales;
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onnx_scales.reserve(scales.size());
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for (auto i : scales) {
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onnx_scales.push_back(i / 127);
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}
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std::vector<int64_t> onnx_zeros(onnx_scales.size(), 0);
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std::string scale_node, zero_node;
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if (onnx_scales.size() == 1) {
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scale_node = helper_->Constant({}, ONNX_NAMESPACE::TensorProto::FLOAT,
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onnx_scales[0]);
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zero_node =
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helper_->Constant({}, ONNX_NAMESPACE::TensorProto::INT8, onnx_zeros[0]);
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} else {
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scale_node =
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helper_->Constant(ONNX_NAMESPACE::TensorProto::FLOAT, onnx_scales);
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zero_node =
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helper_->Constant(ONNX_NAMESPACE::TensorProto::INT8, onnx_zeros);
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}
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auto node = helper_->MakeNode("QuantizeLinear",
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{x_info[0].name, scale_node, zero_node},
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{GetOutput("Y")[0].name});
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if (helper_->GetOpsetVersion() >= 13) {
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AddAttribute(node, "axis", quant_axis_);
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}
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QuantizeInfo quantize_info(onnx_scales, onnx_zeros, scale_node, zero_node,
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quant_axis_);
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helper_->quantize_info[x_info[0].name] = quantize_info;
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}
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} // namespace paddle2onnx
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