// Copyright (c) 2018 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 #include #include #include #include #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/recordio/scanner.h" #include "paddle/fluid/recordio/writer.h" namespace paddle { namespace framework { TEST(LoD, data) { LoD lod{{0, 1, 2}}; lod.push_back({0, 2, 4, 5}); lod.push_back(std::vector({0, 1, 6, 8, 10, 11})); auto& v = lod[0]; for (size_t i = 0; i < v.size(); ++i) { EXPECT_EQ(v[i], i); } } TEST(LodExpand, test) { LoD lod{{0, 2}}; LoDTensor tensor; tensor.set_lod(lod); tensor.Resize({2, 1}); tensor.mutable_data(platform::CPUPlace()); tensor.data()[0] = 0; tensor.data()[1] = 1; LoD target; target.emplace_back(std::vector{0, 3, 5}); auto new_tensor = LodExpand(tensor, target, 0UL, platform::CPUPlace()); std::vector result{{0, 0, 0, 1, 1}}; for (size_t i = 0; i < 5; i++) { ASSERT_EQ(new_tensor.data()[i], result[i]); } } TEST(LoD, GetFineGrainedLoDLength) { LoD lod; lod.push_back(std::vector({0, 2, 4, 5})); lod.push_back(std::vector({0, 1, 6, 8, 10, 11})); lod.push_back( std::vector({0, 2, 5, 7, 10, 12, 15, 17, 20, 24, 26, 29})); auto lod_and_offset = paddle::framework::GetSubLoDAndAbsoluteOffset(lod, 1, 2, 0); LoD lod_length = lod_and_offset.first; size_t start_offset = lod_and_offset.second.first; size_t end_offset = lod_and_offset.second.second; LoD expected; expected.push_back(std::vector{2}); expected.push_back(std::vector{2, 2}); expected.push_back(std::vector{2, 3, 4, 2}); EXPECT_EQ(lod_length, expected); EXPECT_EQ(start_offset, 15UL); EXPECT_EQ(end_offset, 26UL); } TEST(LoD, AppendLoD) { LoD lod_lens; lod_lens.push_back(std::vector({2})); lod_lens.push_back(std::vector({2, 2})); lod_lens.push_back(std::vector({2, 3, 4, 2})); LoD origin; origin.push_back(std::vector({0, 2})); origin.push_back(std::vector({0, 1, 6})); origin.push_back(std::vector({0, 2, 5, 7, 10, 12, 15})); paddle::framework::AppendLoD(&origin, lod_lens); LoD expected; expected.push_back(std::vector({0, 2, 4})); expected.push_back(std::vector({0, 1, 6, 8, 10})); expected.push_back( std::vector({0, 2, 5, 7, 10, 12, 15, 17, 20, 24, 26})); EXPECT_EQ(origin, expected); } TEST(LoD, ToAbsOffset) { LoD relative_lod; relative_lod.push_back(std::vector({0, 2})); relative_lod.push_back(std::vector({0, 1, 3})); relative_lod.push_back(std::vector({0, 2, 4, 5})); LoD abs_lod = paddle::framework::ToAbsOffset(relative_lod); LoD expected; expected.push_back(std::vector({0, 5})); expected.push_back(std::vector({0, 2, 5})); expected.push_back(std::vector({0, 2, 4, 5})); EXPECT_EQ(abs_lod, expected); } TEST(LoD, SplitLoDTensor) { LoD lod; lod.push_back(std::vector({0, 2, 4, 5, 6})); lod.push_back(std::vector({0, 1, 6, 8, 13, 15, 20})); platform::CPUPlace place; LoDTensor lod_tensor; lod_tensor.Resize({20, 1}); float* dst_ptr = lod_tensor.mutable_data(place); for (int i = 0; i < lod_tensor.numel(); ++i) { dst_ptr[i] = i; } lod_tensor.set_lod(lod); std::vector places{platform::CPUPlace(), platform::CPUPlace()}; LoD lod0; lod0.push_back(std::vector({0, 2, 4})); lod0.push_back(std::vector({0, 1, 6, 8, 13})); LoD lod1; lod1.push_back(std::vector({0, 1, 2})); lod1.push_back(std::vector({0, 2, 7})); auto lods = lod_tensor.SplitLoDTensor(places); EXPECT_EQ(lods[0].lod(), lod0); EXPECT_EQ(lods[1].lod(), lod1); } TEST(LoD, MergeLoDTensor) { LoD lod; lod.push_back(std::vector({0, 2, 4, 5, 6})); lod.push_back(std::vector({0, 1, 6, 8, 13, 15, 20})); platform::CPUPlace place; LoDTensor lod_tensor0; LoD lod0; lod0.push_back(std::vector({0, 2, 4})); lod0.push_back(std::vector({0, 1, 6, 8, 13})); lod_tensor0.set_lod(lod0); lod_tensor0.Resize({13, 1}); float* dst_ptr = lod_tensor0.mutable_data(place); for (int i = 0; i < lod_tensor0.numel(); ++i) { dst_ptr[i] = i; } LoDTensor lod_tensor1; LoD lod1; lod1.push_back(std::vector({0, 1, 2})); lod1.push_back(std::vector({0, 2, 7})); lod_tensor1.set_lod(lod1); lod_tensor1.Resize({7, 1}); dst_ptr = lod_tensor1.mutable_data(place); for (int i = 0; i < lod_tensor1.numel(); ++i) { dst_ptr[i] = i; } std::vector lods{&lod_tensor0, &lod_tensor1}; LoDTensor lod_tensor; lod_tensor.MergeLoDTensor(lods, place); EXPECT_EQ(lod_tensor.lod(), lod); } TEST(LoD, CheckLoD) { LoD relative_lod; relative_lod.push_back(std::vector({0, 2})); relative_lod.push_back(std::vector({0, 1, 3})); relative_lod.push_back(std::vector({0, 2, 4, 5})); // check compatible ASSERT_TRUE(CheckLoD(relative_lod)); relative_lod[1].back()++; ASSERT_FALSE(CheckLoD(relative_lod)); relative_lod[1].back()--; // recover it // check empty LoD empty_lod; ASSERT_TRUE(CheckLoD(empty_lod)); // check less than 2 offsets in a level LoD some_lod0; some_lod0.push_back(std::vector({0})); ASSERT_FALSE(CheckLoD(some_lod0)); // check with underlying tensor storage. ASSERT_TRUE(CheckLoD(relative_lod, 5)); ASSERT_FALSE(CheckLoD(relative_lod, 9)); } TEST(LoD, CheckAbsLoD) { LoD relative_lod; relative_lod.push_back(std::vector({0, 2})); relative_lod.push_back(std::vector({0, 1, 3})); relative_lod.push_back(std::vector({0, 2, 4, 5})); auto abs_lod = ToAbsOffset(relative_lod); ASSERT_TRUE(CheckAbsLoD(abs_lod)); // check less than 2 offsets in a level. // check the last item should be compatible with tensor height. abs_lod.back().back()++; ASSERT_FALSE(CheckAbsLoD(abs_lod)); abs_lod.back().back()--; // restore // check less than 2 offsets in a lod. LoD abs_lod0; abs_lod0.push_back(std::vector({0})); ASSERT_FALSE(CheckAbsLoD(abs_lod0)); } TEST(LoDTensor, RecordIO) { LoDTensor tensor; int* tmp = tensor.mutable_data(make_ddim({4, 5}), platform::CPUPlace()); for (int i = 0; i < 20; ++i) { tmp[i] = i; } std::stringstream* stream = new std::stringstream(); auto& ctx = *platform::DeviceContextPool::Instance().Get(platform::CPUPlace()); { recordio::Writer writer(stream, recordio::Compressor::kSnappy); WriteToRecordIO(&writer, {tensor, tensor}, ctx); WriteToRecordIO(&writer, {tensor, tensor}, ctx); writer.Flush(); } auto assert_tensor_ok = [](const LoDTensor& tensor) { for (int i = 0; i < 20; ++i) { ASSERT_EQ(tensor.data()[i], i); } }; { std::unique_ptr stream_ptr(stream); recordio::Scanner scanner(std::move(stream_ptr)); auto tensors = ReadFromRecordIO(&scanner, ctx); ASSERT_EQ(tensors.size(), static_cast(2)); assert_tensor_ok(tensors[0]); assert_tensor_ok(tensors[1]); tensors = ReadFromRecordIO(&scanner, ctx); ASSERT_EQ(tensors.size(), static_cast(2)); assert_tensor_ok(tensors[0]); assert_tensor_ok(tensors[1]); } } } // namespace framework } // namespace paddle