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58 lines
2.1 KiB
C++
58 lines
2.1 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/cumsum.h"
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namespace paddle2onnx {
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REGISTER_MAPPER(cumsum, CumsumMapper)
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int32_t CumsumMapper::GetMinOpset(bool verbose) {
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Logger(verbose, 11) << RequireOpset(11) << std::endl;
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return 11;
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}
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void CumsumMapper::Opset11() {
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auto input_info = GetInput("X");
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auto output_info = GetOutput("Out");
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if (input_info[0].Rank() == 0) {
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auto axis_node = helper_->Constant({}, GetOnnxDtype(P2ODataType::INT64), 0);
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auto unsqueeze_node = helper_->Unsqueeze(input_info[0].name, {0});
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auto cumsum_node = helper_->MakeNode("CumSum", {unsqueeze_node, axis_node});
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if (flatten_) {
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helper_->AutoCast(cumsum_node->output(0), output_info[0].name,
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input_info[0].dtype, output_info[0].dtype);
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} else {
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helper_->Squeeze(cumsum_node->output(0), output_info[0].name, {0});
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}
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} else {
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std::string axis_node;
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if (IsAttrVar("axis")) {
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auto axis_info = GetAttrVar("axis");
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axis_node = helper_->AutoCast(axis_info[0].name, axis_info[0].dtype,
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P2ODataType::INT64);
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} else {
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GetAttr("axis", &axis_);
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axis_node =
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helper_->Constant({}, GetOnnxDtype(P2ODataType::INT64), axis_);
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}
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std::string input_node = input_info[0].name;
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if (flatten_) {
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input_node = helper_->Reshape(input_info[0].name, {-1});
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}
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helper_->MakeNode("CumSum", {input_node, axis_node}, {output_info[0].name});
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}
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}
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} // namespace paddle2onnx
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