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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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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 <gtest/gtest.h>
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#include <fstream>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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void test_pool2d(bool global_pooling, bool ceil_mode,
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std::string pool_type = "max") {
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framework::Scope scope;
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std::unordered_set<std::string> parameters;
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TRTConvertValidation validator(5, parameters, scope, 1 << 15);
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// The ITensor's Dims should not contain the batch size.
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// So, the ITensor's Dims of input and output should be C * H * W.
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validator.DeclInputVar("pool2d-X", nvinfer1::Dims3(3, 6, 7));
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if (global_pooling)
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validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 1, 1));
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else if (ceil_mode)
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validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 3, 4));
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else
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validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 3, 3));
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// Prepare Op description
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framework::OpDesc desc;
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desc.SetType("pool2d");
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desc.SetInput("X", {"pool2d-X"});
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desc.SetOutput("Out", {"pool2d-Out"});
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std::vector<int> ksize({2, 2});
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std::vector<int> strides({2, 2});
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std::vector<int> paddings({0, 0});
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std::string pooling_t = pool_type;
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desc.SetAttr("pooling_type", pooling_t);
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desc.SetAttr("ksize", ksize);
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desc.SetAttr("strides", strides);
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desc.SetAttr("paddings", paddings);
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desc.SetAttr("global_pooling", global_pooling);
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desc.SetAttr("ceil_mode", ceil_mode);
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LOG(INFO) << "set OP";
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validator.SetOp(*desc.Proto());
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LOG(INFO) << "execute";
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validator.Execute(3);
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}
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TEST(Pool2dOpConverter, normal) { test_pool2d(false, false); }
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TEST(Pool2dOpConverter, test_global_pooling) { test_pool2d(true, false); }
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TEST(Pool2dOpConverter, max_ceil_test) { test_pool2d(false, true); }
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TEST(Pool2dOpConverter, avg_ceil_test) { test_pool2d(false, true, "avg"); }
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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USE_OP(pool2d);
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