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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>
68 lines
2.8 KiB
C++
68 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/tensor/dist.h"
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#include <cmath>
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#include <vector>
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namespace paddle2onnx {
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REGISTER_MAPPER(dist, DistMapper)
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const int g_NegIntInfinity = 0xFF800000;
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const float g_NegFloatInfinity = *((float *)&g_NegIntInfinity);
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void DistMapper::Opset7() {
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auto x_info = GetInput("X");
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auto y_info = GetInput("Y");
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auto output_info = GetOutput("Out");
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auto sub_node = helper_->MakeNode("Sub", {x_info[0].name, y_info[0].name});
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auto abs_node = helper_->MakeNode("Abs", {sub_node->output(0)});
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if (fabs(p_) < 1e-6) {
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auto sign_node = helper_->MakeNode("Sign", {abs_node->output(0)});
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auto sum_node = helper_->MakeNode("ReduceSum", {sign_node->output(0)});
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AddAttribute(sum_node, "keepdims", static_cast<int64_t>(0));
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auto s_sum_node = helper_->Reshape(sum_node->output(0), {-1});
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helper_->AutoCast(s_sum_node, output_info[0].name, x_info[0].dtype,
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output_info[0].dtype);
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} else if (p_ == std::numeric_limits<float>::infinity()) {
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auto max_node = helper_->MakeNode("ReduceMax", {abs_node->output(0)});
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AddAttribute(max_node, "keepdims", static_cast<int64_t>(0));
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auto s_max_node = helper_->Reshape(max_node->output(0), {-1});
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helper_->AutoCast(s_max_node, output_info[0].name, x_info[0].dtype,
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output_info[0].dtype);
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} else if (p_ == g_NegFloatInfinity) {
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auto min_node = helper_->MakeNode("ReduceMin", {abs_node->output(0)});
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AddAttribute(min_node, "keepdims", static_cast<int64_t>(0));
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auto s_min_node = helper_->Reshape(min_node->output(0), {-1});
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helper_->AutoCast(s_min_node, output_info[0].name, x_info[0].dtype,
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output_info[0].dtype);
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} else {
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std::string p = helper_->Constant({1}, GetOnnxDtype(x_info[0].dtype), p_);
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auto pow_node = helper_->MakeNode("Pow", {abs_node->output(0), p});
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auto sum_node = helper_->MakeNode("ReduceSum", {pow_node->output(0)});
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AddAttribute(sum_node, "keepdims", static_cast<int64_t>(0));
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auto s_node = helper_->Reshape(sum_node->output(0), {-1});
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auto p_1 = helper_->MakeNode("Reciprocal", {p});
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helper_->MakeNode("Pow", {s_node, p_1->output(0)}, {output_info[0].name});
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}
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}
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} // namespace paddle2onnx
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