wehub-resource-sync
48 lines
1.7 KiB
C++
48 lines
1.7 KiB
C++
/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 "paddle/fluid/inference/tensorrt/convert/op_converter.h"
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namespace paddle::inference::tensorrt {
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/*
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* TransposeOp
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*/
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class TransposeOpConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope,
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bool test_mode) override {
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VLOG(3) << "convert a transpose op to tensorrt shuffle layer";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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int dims = input->getDimensions().nbDims;
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std::vector<int> axis =
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PADDLE_GET_CONST(std::vector<int>, op_desc.GetAttr("axis"));
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nvinfer1::Permutation perm;
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for (int i = 0; i < dims; i++) {
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int j = i;
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perm.order[i] = axis[j];
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}
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auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input);
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layer->setFirstTranspose(perm);
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auto output_name = op_desc.Output("Out")[0];
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ReplenishLayerAndOutput(layer, "transpose", {output_name}, test_mode);
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(transpose, TransposeOpConverter);
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REGISTER_TRT_OP_CONVERTER(transpose2, TransposeOpConverter);
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