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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>
76 lines
2.6 KiB
C++
76 lines
2.6 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/tensor/linspace.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(linspace, LinspaceMapper)
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int32_t LinspaceMapper::GetMinOpset(bool verbose) {
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Logger(verbose, 9) << RequireOpset(9) << std::endl;
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return 9;
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};
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void LinspaceMapper::Opset9() {
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auto start_info = GetInput("Start");
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auto stop_info = GetInput("Stop");
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auto num_info = GetInput("Num");
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auto output_info = GetOutput("Out");
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std::string cast_start = helper_->AutoCast(
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start_info[0].name, start_info[0].dtype, P2ODataType::FP32);
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std::string cast_stop = helper_->AutoCast(
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stop_info[0].name, stop_info[0].dtype, P2ODataType::FP32);
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auto sub_a_node = helper_->MakeNode("Sub", {cast_stop, cast_start});
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std::string one_node = helper_->Constant(GetOnnxDtype(num_info[0].dtype),
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std::vector<int32_t>(1, 1));
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auto sub_b_node = helper_->MakeNode("Sub", {num_info[0].name, one_node});
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std::string sub_b_float_node = helper_->AutoCast(
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sub_b_node->output(0), num_info[0].dtype, P2ODataType::FP32);
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auto step =
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helper_->MakeNode("Div", {sub_a_node->output(0), sub_b_float_node});
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std::string range_tensor = helper_->AutoCast(
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num_info[0].name, num_info[0].dtype, P2ODataType::INT64);
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std::string one_like_node = helper_->ConstOfShape(
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range_tensor, GetOnnxDtype(P2ODataType::FP32), static_cast<float>(1));
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auto none_zero_node = helper_->MakeNode("NonZero", {one_like_node});
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std::string trans_squeeze =
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helper_->Squeeze(none_zero_node->output(0), std::vector<int64_t>(1, 0));
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std::string cast_trans_squeeze =
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helper_->AutoCast(trans_squeeze, P2ODataType::INT64, P2ODataType::FP32);
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auto mul_node =
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helper_->MakeNode("Mul", {cast_trans_squeeze, step->output(0)});
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auto add_node = helper_->MakeNode("Add", {mul_node->output(0), cast_start});
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helper_->AutoCast(add_node->output(0), output_info[0].name, P2ODataType::FP32,
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output_info[0].dtype);
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}
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} // namespace paddle2onnx
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