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[oneDNN] Fix adaptive Pooling (#58361)
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| /* Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
| #include <gtest/gtest.h> | ||
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| #include <fstream> | ||
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| #include "paddle/fluid/framework/lod_tensor.h" | ||
| #include "paddle/fluid/framework/naive_executor.h" | ||
| #include "paddle/fluid/framework/op_registry.h" | ||
| #include "paddle/fluid/framework/operator.h" | ||
| #include "paddle/fluid/framework/scope.h" | ||
| #include "paddle/phi/common/place.h" | ||
| #include "paddle/phi/core/enforce.h" | ||
| #include "paddle/phi/core/kernel_registry.h" | ||
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| namespace paddle { | ||
| namespace inference { | ||
| namespace tensorrt { | ||
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| template <typename DataType> | ||
| void AddVarToScope(const std::string var_name, | ||
| paddle::framework::Scope* scope, | ||
| const paddle::framework::DDim& dims) { | ||
| std::random_device seed; | ||
| std::default_random_engine engine(seed()); | ||
| std::uniform_real_distribution<float> dist(0, 100); | ||
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| phi::DenseTensor tmp_tensor; | ||
| auto* tmp_data = | ||
| tmp_tensor.mutable_data<DataType>(dims, paddle::platform::CPUPlace()); | ||
| auto* tensor = scope->Var(var_name)->GetMutable<phi::DenseTensor>(); | ||
| tensor->mutable_data<DataType>(dims, paddle::platform::CPUPlace()); | ||
| for (auto i = 0; i < tensor->numel(); ++i) { | ||
| tmp_data[i] = static_cast<DataType>(dist(engine)); | ||
| } | ||
| paddle::framework::TensorCopySync( | ||
| tmp_tensor, paddle::platform::CPUPlace(), tensor); | ||
| } | ||
| void test_pool2d(bool adaptive, bool ceil_mode, std::string pool_type = "max") { | ||
| framework::Scope scope; | ||
| paddle::platform::CPUPlace cpu_place; | ||
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| // Prepare Op description | ||
| framework::OpDesc desc; | ||
| desc.SetType("pool2d"); | ||
| desc.SetInput("X", {"pool2d-X"}); | ||
| desc.SetOutput("Out", {"pool2d-Out"}); | ||
| AddVarToScope<float>("pool2d-X", &scope, {1, 3, 9, 12}); | ||
| AddVarToScope<float>("pool2d-Out", &scope, {1, 3, 2, 2}); | ||
| std::vector<int> ksize({2, 2}); | ||
| std::vector<int> strides({1, 1}); | ||
| std::vector<int> paddings({0, 0}); | ||
| std::string pooling_t = pool_type; | ||
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| desc.SetAttr("pooling_type", pooling_t); | ||
| desc.SetAttr("ksize", ksize); | ||
| desc.SetAttr("strides", strides); | ||
| desc.SetAttr("paddings", paddings); | ||
| desc.SetAttr("adaptive", adaptive); | ||
| desc.SetAttr("ceil_mode", ceil_mode); | ||
| desc.SetAttr("use_mkldnn", true); | ||
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| auto op = paddle::framework::OpRegistry::CreateOp(desc); | ||
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| op->Run(scope, cpu_place); | ||
| } | ||
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| TEST(Pool2dOpConverter, normal) { test_pool2d(false, false); } | ||
| TEST(Pool2dOpConverter, adaptive) { test_pool2d(true, false); } | ||
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| TEST(Pool2dOpConverter, max_ceil_test) { test_pool2d(false, true); } | ||
| TEST(Pool2dOpConverter, avg_ceil_test) { test_pool2d(true, true, "avg"); } | ||
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| } // namespace tensorrt | ||
| } // namespace inference | ||
| } // namespace paddle | ||
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| USE_OP_ITSELF(pool2d); | ||
| PD_DECLARE_KERNEL(pool2d, OneDNN, ONEDNN); | ||
| PD_DECLARE_KERNEL(pool2d, CPU, ALL_LAYOUT); |