/* Copyright (c) 2016 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 "paddle/fluid/operators/beam_search_decode_op_xpu.h" #include "gtest/gtest.h" using CPUPlace = paddle::platform::CPUPlace; using XPUPlace = paddle::platform::XPUPlace; using LoD = paddle::framework::LoD; using LoDTensorArray = paddle::framework::LoDTensorArray; template using BeamSearchDecoder = paddle::operators::BeamSearchDecoder; template using Sentence = paddle::operators::Sentence; template using SentenceVector = paddle::operators::SentenceVector; namespace paddle { namespace test { template void GenerateXPUExample(const std::vector& level_0, const std::vector& level_1, const std::vector& data, LoDTensorArray* ids, LoDTensorArray* scores) { PADDLE_ENFORCE_EQ(level_0.back(), level_1.size() - 1, platform::errors::InvalidArgument( "source level is used to describe candidate set" ", so it's element should less than levle_1 length. " "And the value of source" "level is %d. ", level_1.size() - 1)); PADDLE_ENFORCE_EQ(level_1.back(), data.size(), platform::errors::InvalidArgument( "the lowest level is used to describe data" ", so it's last element should be data length %d. ", data.size())); CPUPlace place; int XPU_PlaceNo = 0; if (std::getenv("FLAGS_selected_xpus") != nullptr) XPU_PlaceNo = atoi(std::getenv("FLAGS_selected_xpus")); else if (std::getenv("XPU_VISIBLE_DEVICES") != nullptr) XPU_PlaceNo = atoi(std::getenv("XPU_VISIBLE_DEVICES")); XPUPlace xpu_place(XPU_PlaceNo); LoD lod; lod.push_back(level_0); lod.push_back(level_1); // Ids phi::DenseTensor tensor_id_cpu; tensor_id_cpu.set_lod(lod); tensor_id_cpu.Resize({static_cast(data.size())}); // malloc memory int64_t* id_cpu_ptr = tensor_id_cpu.mutable_data(place); for (size_t i = 0; i < data.size(); ++i) { id_cpu_ptr[i] = static_cast(data.at(i)); } phi::DenseTensor tensor_id; const phi::DenseTensorMeta meta_data_id(phi::DataType::INT64, tensor_id_cpu.dims()); tensor_id.set_meta(meta_data_id); tensor_id.set_lod(lod); int64_t* id_ptr = tensor_id.mutable_data(xpu_place); paddle::memory::Copy(paddle::platform::XPUPlace(XPU_PlaceNo), id_ptr, paddle::platform::CPUPlace(), id_cpu_ptr, tensor_id_cpu.numel() * sizeof(int64_t)); // Scores phi::DenseTensor tensor_score_cpu; tensor_score_cpu.set_lod(lod); tensor_score_cpu.Resize({static_cast(data.size())}); // malloc memory T* score_cpu_ptr = tensor_score_cpu.mutable_data(place); for (size_t i = 0; i < data.size(); ++i) { score_cpu_ptr[i] = static_cast(data.at(i)); } phi::DenseTensor tensor_score; if (std::is_same::value) { const phi::DenseTensorMeta meta_data_score(phi::DataType::FLOAT32, tensor_score_cpu.dims()); tensor_score.set_meta(meta_data_score); } else if (std::is_same::value) { const phi::DenseTensorMeta meta_data_score(phi::DataType::FLOAT64, tensor_score_cpu.dims()); tensor_score.set_meta(meta_data_score); } else if (std::is_same::value) { const phi::DenseTensorMeta meta_data_score(phi::DataType::FLOAT16, tensor_score_cpu.dims()); tensor_score.set_meta(meta_data_score); } else if (std::is_same::value) { const phi::DenseTensorMeta meta_data_score(phi::DataType::INT32, tensor_score_cpu.dims()); tensor_score.set_meta(meta_data_score); } else if (std::is_same::value) { const phi::DenseTensorMeta meta_data_score(phi::DataType::INT64, tensor_score_cpu.dims()); tensor_score.set_meta(meta_data_score); } tensor_score.set_lod(lod); T* score_ptr = tensor_score.mutable_data(xpu_place); paddle::memory::Copy(paddle::platform::XPUPlace(XPU_PlaceNo), score_ptr, paddle::platform::CPUPlace(), score_cpu_ptr, tensor_score_cpu.numel() * sizeof(T)); ids->push_back(tensor_id); scores->push_back(tensor_score); } template void BeamSearchDecodeTestByXPUFrame() { CPUPlace place; // Construct sample data with 5 steps and 2 source sentences // beam_size = 2, start_id = 0, end_id = 1 LoDTensorArray ids; LoDTensorArray scores; GenerateXPUExample(std::vector{0, 1, 2}, std::vector{0, 1, 2}, std::vector{0, 0}, &ids, &scores); // start with start_id GenerateXPUExample(std::vector{0, 1, 2}, std::vector{0, 2, 4}, std::vector{2, 3, 4, 5}, &ids, &scores); GenerateXPUExample(std::vector{0, 2, 4}, std::vector{0, 2, 2, 4, 4}, std::vector{3, 1, 5, 4}, &ids, &scores); GenerateXPUExample(std::vector{0, 2, 4}, std::vector{0, 1, 2, 3, 4}, std::vector{1, 1, 3, 5}, &ids, &scores); GenerateXPUExample( std::vector{0, 2, 4}, std::vector{0, 0, 0, 2, 2}, // the branchs of the first source // sentence are pruned since finished std::vector{5, 1}, &ids, &scores); ASSERT_EQ(ids.size(), 5UL); ASSERT_EQ(scores.size(), 5UL); phi::DenseTensor id_tensor_cpu; phi::DenseTensor score_tensor_cpu; paddle::operators::BeamSearchDecodeXPUFunctor bs_xpu( ids, scores, &id_tensor_cpu, &score_tensor_cpu, 2, 1); bs_xpu.apply_xpu(); LoD lod = id_tensor_cpu.lod(); std::vector expect_source_lod = {0, 2, 4}; ASSERT_EQ(lod[0], expect_source_lod); std::vector expect_sentence_lod = {0, 4, 7, 12, 17}; ASSERT_EQ(lod[1], expect_sentence_lod); std::vector expect_data = { 0, 2, 3, 1, 0, 2, 1, 0, 4, 5, 3, 5, 0, 4, 5, 3, 1}; ASSERT_EQ(id_tensor_cpu.dims()[0], static_cast(expect_data.size())); for (size_t i = 0; i < expect_data.size(); ++i) { ASSERT_EQ(id_tensor_cpu.data()[i], static_cast(expect_data[i])); } for (int64_t i = 0; i < id_tensor_cpu.dims()[0]; ++i) { ASSERT_EQ(score_tensor_cpu.data()[i], static_cast(id_tensor_cpu.data()[i])); } } } // namespace test } // namespace paddle TEST(BeamSearchDecodeOpXPU, Backtrace_XPU_Float) { paddle::test::BeamSearchDecodeTestByXPUFrame(); } TEST(BeamSearchDecodeOpXPU, Backtrace_XPU_Float16) { paddle::test::BeamSearchDecodeTestByXPUFrame(); } TEST(BeamSearchDecodeOpXPU, Backtrace_XPU_Int) { paddle::test::BeamSearchDecodeTestByXPUFrame(); } TEST(BeamSearchDecodeOpXPU, Backtrace_XPU_Int64) { paddle::test::BeamSearchDecodeTestByXPUFrame(); } TEST(BeamSearchDecodeOpXPU, Backtrace_XPU_Double) { paddle::test::BeamSearchDecodeTestByXPUFrame(); }