[Paddle-TRT] gather converter (#31640)
* trt gather converter * add trt gather unit_testtest_benchmark_ci
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/* Copyright (c) 2018 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 {
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namespace framework {
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class Scope;
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namespace proto {
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class OpDesc;
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} // namespace proto
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} // namespace framework
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} // namespace paddle
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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/*
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* Gather Op
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*/
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class GatherOpConverter : 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, bool test_mode) override {
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VLOG(3) << "convert a fluid gather op to tensorrt gather layer";
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framework::OpDesc op_desc(op, nullptr);
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std::string input_name = op_desc.Input("X").front();
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std::string index_name = op_desc.Input("Index").front();
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std::string output_name = op_desc.Output("Out").front();
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const auto input_tensor = engine_->GetITensor(input_name);
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const auto index_tensor = engine_->GetITensor(index_name);
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const int axis = 0;
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auto layer = TRT_ENGINE_ADD_LAYER(engine_, Gather, *input_tensor,
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*index_tensor, axis);
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auto odim = layer->getOutput(0)->getDimensions();
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auto reshape_layer =
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TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *layer->getOutput(0));
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nvinfer1::Dims target_shape{};
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target_shape.nbDims = odim.nbDims - 1;
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for (int i = 0; i < axis; ++i) {
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target_shape.d[i] = odim.d[i];
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}
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target_shape.d[axis] = 0;
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for (int i = axis + 1; i < target_shape.nbDims; ++i) {
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target_shape.d[i] = odim.d[i + 1];
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}
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reshape_layer->setReshapeDimensions(target_shape);
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RreplenishLayerAndOutput(reshape_layer, "gather", {output_name}, test_mode);
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}
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};
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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REGISTER_TRT_OP_CONVERTER(gather, GatherOpConverter);
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@ -0,0 +1,70 @@
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# Copyright (c) 2020 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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from __future__ import print_function
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import unittest
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import numpy as np
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from inference_pass_test import InferencePassTest
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.core import PassVersionChecker
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from paddle.fluid.core import AnalysisConfig
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class TRTGatherTest(InferencePassTest):
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def setUp(self):
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self.set_params()
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with fluid.program_guard(self.main_program, self.startup_program):
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data = fluid.data(name='data', shape=[-1, 512], dtype='float32')
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index = fluid.data(name='index', shape=[-1], dtype='int32')
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scale_out = self.append_gather(data, index)
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out = fluid.layers.batch_norm(scale_out, is_test=True)
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index = np.arange(self.num_gather, dtype='int32')
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np.random.shuffle(index)
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self.feeds = {
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"data": np.random.random([self.bs, 512]).astype("float32"),
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"index": index,
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}
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self.enable_trt = True
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self.trt_parameters = TRTGatherTest.TensorRTParam(
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1 << 30, self.bs, 1, AnalysisConfig.Precision.Float32, False, False)
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self.fetch_list = [out]
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def set_params(self):
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self.num_gather = 16
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self.bs = 32
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def append_gather(self, data, index):
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return fluid.layers.gather(data, index=index)
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def test_check_output(self):
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if core.is_compiled_with_cuda():
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use_gpu = True
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self.check_output_with_option(use_gpu, flatten=True)
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self.assertTrue(
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PassVersionChecker.IsCompatible('tensorrt_subgraph_pass'))
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class TRTGatherTest1(TRTGatherTest):
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def set_params(self):
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self.num_gather = 32
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self.bs = 32
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if __name__ == "__main__":
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unittest.main()
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