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84 lines
2.9 KiB
C++
84 lines
2.9 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/scatter.h"
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namespace paddle2onnx {
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REGISTER_MAPPER(scatter, ScatterMapper)
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int32_t ScatterMapper::GetMinOpset(bool verbose) {
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if (!overwrite_) {
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Logger(verbose, 16) << "When overwrite is False, " << RequireOpset(16)
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<< std::endl;
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return 16;
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}
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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 ScatterMapper::Opset11() {
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auto input_x_info = GetInput("X");
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auto input_ids_info = GetInput("Ids");
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auto input_updates_info = GetInput("Updates");
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auto output_info = GetOutput("Out");
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std::string ids_node = helper_->AutoCast(
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input_ids_info[0].name, input_ids_info[0].dtype, P2ODataType::INT64);
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std::string shape_node;
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if (input_ids_info[0].Rank() == 0) {
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std::vector<int64_t> shape = {1};
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shape_node = helper_->Constant(GetOnnxDtype(P2ODataType::INT64), shape);
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} else {
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std::vector<int64_t> shape = {input_ids_info[0].shape[0], 1};
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shape_node = helper_->Constant(GetOnnxDtype(P2ODataType::INT64), shape);
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}
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auto reshape_index_node =
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helper_->MakeNode("Reshape", {ids_node, shape_node});
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if (!overwrite_) {
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auto shape_node = helper_->MakeNode("Shape", {input_x_info[0].name});
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std::string zeros_like_node = helper_->ConstOfShape(
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shape_node->output(0), GetOnnxDtype(input_x_info[0].dtype),
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static_cast<float>(0));
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auto scatter_nd_node = helper_->MakeNode(
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"ScatterND", {zeros_like_node, reshape_index_node->output(0),
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input_updates_info[0].name});
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AddAttribute(scatter_nd_node, "reduction", "add");
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std::string zero_node = helper_->Constant(
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{}, GetOnnxDtype(input_x_info[0].dtype), static_cast<float>(0));
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auto equal_node =
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helper_->MakeNode("Equal", {scatter_nd_node->output(0), zero_node});
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std::string condition_node = helper_->AutoCast(
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equal_node->output(0), P2ODataType::INT64, P2ODataType::BOOL);
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helper_->MakeNode(
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"Where",
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{condition_node, input_x_info[0].name, scatter_nd_node->output(0)},
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{output_info[0].name});
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} else {
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auto node =
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helper_->MakeNode("ScatterND",
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{input_x_info[0].name, reshape_index_node->output(0),
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input_updates_info[0].name},
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{output_info[0].name});
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}
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}
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} // namespace paddle2onnx
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