/* Copyright (c) 2022 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 "paddle/phi/api/include/strings_api.h" #include "paddle/phi/api/lib/utils/allocator.h" #include "paddle/phi/backends/all_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/string_tensor.h" PD_DECLARE_KERNEL(strings_lower, CPU, ALL_LAYOUT); PD_DECLARE_KERNEL(strings_upper, CPU, ALL_LAYOUT); namespace paddle { namespace tests { using phi::CPUPlace; using phi::StringTensor; using phi::StringTensorMeta; TEST(API, case_convert) { auto cpu = CPUPlace(); const auto alloc = std::make_shared(cpu); // 1. create tensor const phi::DDim dims({1, 2}); StringTensorMeta meta(dims); auto cpu_strings_x = std::make_shared( alloc.get(), phi::StringTensorMeta(meta)); phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance(); auto* dev_ctx = pool.Get(phi::CPUPlace()); pstring* cpu_strings_x_data = dev_ctx->template Alloc(cpu_strings_x.get()); std::string strs[] = {"A Short Pstring.", "A Large Pstring Whose Length Is Longer Than 22."}; for (int i = 0; i < 2; ++i) { cpu_strings_x_data[i] = strs[i]; } // 2. get expected results std::string expected_results[] = {strs[0], strs[0], strs[1], strs[1]}; std::transform( strs[0].begin(), strs[0].end(), expected_results[0].begin(), ::tolower); std::transform( strs[0].begin(), strs[0].end(), expected_results[1].begin(), ::toupper); std::transform( strs[1].begin(), strs[1].end(), expected_results[2].begin(), ::tolower); std::transform( strs[1].begin(), strs[1].end(), expected_results[3].begin(), ::toupper); // 3. test API, ascii encoding paddle::experimental::Tensor x(cpu_strings_x); auto lower_out = paddle::experimental::strings::lower(x, false); auto upper_out = paddle::experimental::strings::upper(x, false); auto lower_tensor = std::dynamic_pointer_cast(lower_out.impl()); auto upper_tensor = std::dynamic_pointer_cast(upper_out.impl()); ASSERT_EQ(lower_tensor->dims(), dims); ASSERT_EQ(upper_tensor->dims(), dims); auto lower_tensor_ptr = lower_tensor->data(); auto upper_tensor_ptr = upper_tensor->data(); const std::string cpu_results[] = {lower_tensor_ptr[0].data(), upper_tensor_ptr[0].data(), lower_tensor_ptr[1].data(), upper_tensor_ptr[1].data()}; for (int i = 0; i < 4; ++i) { ASSERT_EQ(cpu_results[i], expected_results[i]); } } TEST(API, case_convert_utf8) { auto cpu = CPUPlace(); const auto alloc = std::make_shared(cpu); // 1. create tensor const phi::DDim dims({1, 2}); StringTensorMeta meta(dims); auto cpu_strings_x = std::make_shared( alloc.get(), phi::StringTensorMeta(meta)); phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance(); auto* dev_ctx = pool.Get(phi::CPUPlace()); pstring* cpu_strings_x_data = dev_ctx->template Alloc(cpu_strings_x.get()); std::string strs[] = {"óÓsscHloëË", "óÓsscHloëËóÓsscHloëËóÓsscHloëË"}; for (int i = 0; i < 2; ++i) { cpu_strings_x_data[i] = strs[i]; } // 2. get expected results std::string expected_results[] = {"óósschloëë", "ÓÓSSCHLOËË", "óósschloëëóósschloëëóósschloëë", "ÓÓSSCHLOËËÓÓSSCHLOËËÓÓSSCHLOËË"}; // 3. test API, ascii encoding paddle::experimental::Tensor x(cpu_strings_x); auto lower_out = paddle::experimental::strings::lower(x, true); auto upper_out = paddle::experimental::strings::upper(x, true); auto lower_tensor = std::dynamic_pointer_cast(lower_out.impl()); auto upper_tensor = std::dynamic_pointer_cast(upper_out.impl()); ASSERT_EQ(lower_tensor->dims(), dims); ASSERT_EQ(upper_tensor->dims(), dims); auto lower_tensor_ptr = lower_tensor->data(); auto upper_tensor_ptr = upper_tensor->data(); const char* cpu_results[] = {lower_tensor_ptr[0].data(), upper_tensor_ptr[0].data(), lower_tensor_ptr[1].data(), upper_tensor_ptr[1].data()}; for (int i = 0; i < 4; ++i) { ASSERT_EQ(std::string(cpu_results[i]), expected_results[i]); } } } // namespace tests } // namespace paddle