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75 lines
2.5 KiB
75 lines
2.5 KiB
// Copyright (c) 2018 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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#pragma once
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#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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class SplitPlugin : public PluginTensorRT {
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int axis_;
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std::vector<int> output_length_;
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int nx_, ny_, nz_;
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std::vector<int> segment_offsets_;
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protected:
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virtual size_t getSerializationSize() override {
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return SerializedSize(axis_) + SerializedSize(output_length_) +
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getBaseSerializationSize();
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}
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// TRT will call this func when we need to serialize the configuration of
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// tensorrt.
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// It should not be called by users.
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virtual void serialize(void *buffer) override {
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serializeBase(buffer);
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SerializeValue(&buffer, axis_);
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SerializeValue(&buffer, output_length_);
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}
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public:
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SplitPlugin(int axis, std::vector<int> const &output_lengths)
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: axis_(axis), output_length_(output_lengths) {
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assert(axis <= nvinfer1::Dims::MAX_DIMS);
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}
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// It was used for tensorrt deserialization.
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// It should not be called by users.
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SplitPlugin(void const *serialData, size_t serialLength) {
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deserializeBase(serialData, serialLength);
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DeserializeValue(&serialData, &serialLength, &axis_);
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DeserializeValue(&serialData, &serialLength, &output_length_);
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}
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SplitPlugin *clone() const override {
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return new SplitPlugin(axis_, output_length_);
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}
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virtual const char *getPluginType() const override { return "split"; }
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virtual int getNbOutputs() const override { return output_length_.size(); }
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virtual nvinfer1::Dims getOutputDimensions(int index,
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const nvinfer1::Dims *inputs,
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int nbInputDims) override;
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virtual int initialize() override;
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virtual int enqueue(int batchSize, const void *const *inputs, void **outputs,
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void *workspace, cudaStream_t stream) override;
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};
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} // tensorrt
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} // inference
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} // paddle
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