text: /* Copyright (c) 2021 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>
  
  #include <memory>
  
  #include "paddle/fluid/memory/allocation/allocator_facade.h"
  #include "paddle/phi/api/lib/utils/allocator.h"
  #include "paddle/phi/backends/cpu/cpu_context.h"
  #include "paddle/phi/core/dense_tensor.h"
  #include "paddle/phi/core/kernel_registry.h"
  #include "paddle/phi/kernels/empty_kernel.h"
  #include "paddle/phi/kernels/full_kernel.h"
  
  namespace phi {
  namespace tests {
  
  namespace framework = paddle::framework;
  using DDim = phi::DDim;
  
  TEST(DEV_API, empty) {
    // 1. create input
    phi::CPUContext dev_ctx;
    dev_ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
                             .GetAllocator(paddle::platform::CPUPlace())
                             .get());
    dev_ctx.Init();
  
    // 2. test API
    auto out = phi::Empty<int>(dev_ctx, {3, 2});
  
    // 3. check result
    ASSERT_EQ(out.dims().size(), 2);
    ASSERT_EQ(out.dims()[0], 3);
    ASSERT_EQ(out.numel(), 6);
    ASSERT_EQ(out.meta().dtype, phi::DataType::INT32);
    ASSERT_EQ(out.meta().layout, phi::DataLayout::NCHW);
  }
  
  TEST(DEV_API, empty_like) {
    // 1. create tensor
    const auto alloc = std::make_unique<paddle::experimental::DefaultAllocator>(
        paddle::platform::CPUPlace());
    phi::DenseTensor dense_x(alloc.get(),
                             phi::DenseTensorMeta(phi::DataType::FLOAT32,
                                                  phi::make_ddim({3, 2}),
                                                  phi::DataLayout::NCHW));
    auto* dense_x_data =
        dense_x.mutable_data<float>(paddle::platform::CPUPlace());
    dense_x_data[0] = 0;
  
    // 2. test API
    phi::CPUContext dev_ctx;
    dev_ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
                             .GetAllocator(paddle::platform::CPUPlace())
                             .get());
    dev_ctx.Init();
    auto out = phi::EmptyLike<float>(dev_ctx, dense_x);
  
    // 3. check result
    ASSERT_EQ(out.dims().size(), 2);
    ASSERT_EQ(out.dims()[0], 3);
    ASSERT_EQ(out.numel(), 6);
    ASSERT_EQ(out.meta().dtype, phi::DataType::FLOAT32);
    ASSERT_EQ(out.meta().layout, phi::DataLayout::NCHW);
  }
  
  TEST(DEV_API, full) {
    // 1. create input
    float val = 1.0;
  
    // 2. test API
    phi::CPUContext dev_ctx;
    dev_ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
                             .GetAllocator(paddle::platform::CPUPlace())
                             .get());
    dev_ctx.Init();
    auto out = phi::Full<float>(dev_ctx, {3, 2}, val);
  
    // 3. check result
    ASSERT_EQ(out.dims().size(), 2);
    ASSERT_EQ(out.dims()[0], 3);
    ASSERT_EQ(out.numel(), 6);
    ASSERT_EQ(out.meta().dtype, phi::DataType::FLOAT32);
    ASSERT_EQ(out.meta().layout, phi::DataLayout::NCHW);
  
    auto* actual_result = out.data<float>();
    for (auto i = 0; i < 6; i++) {
      ASSERT_NEAR(actual_result[i], val, 1e-6f);
    }
  }
  
  TEST(DEV_API, full_like) {
    // 1. create tensor
    const auto alloc = std::make_unique<paddle::experimental::DefaultAllocator>(
        paddle::platform::CPUPlace());
    phi::DenseTensor dense_x(alloc.get(),
                             phi::DenseTensorMeta(phi::DataType::FLOAT32,
                                                  phi::make_ddim({3, 2}),
                                                  phi::DataLayout::NCHW));
    auto* dense_x_data =
        dense_x.mutable_data<float>(paddle::platform::CPUPlace());
    dense_x_data[0] = 0;
    float val = 1.0;
  
    phi::CPUContext dev_ctx;
    dev_ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
                             .GetAllocator(paddle::platform::CPUPlace())
                             .get());
    dev_ctx.Init();
  
    // 2. test API
    auto out = phi::FullLike<float>(dev_ctx, dense_x, val);
  
    // 3. check result
    ASSERT_EQ(out.dims().size(), 2);
    ASSERT_EQ(out.dims()[0], 3);
    ASSERT_EQ(out.numel(), 6);
    ASSERT_EQ(out.meta().dtype, phi::DataType::FLOAT32);
    ASSERT_EQ(out.meta().layout, phi::DataLayout::NCHW);
  
    auto* actual_result = out.data<float>();
    for (auto i = 0; i < 6; i++) {
      ASSERT_NEAR(actual_result[i], val, 1e-6f);
    }
  }
  
  }  // namespace tests
  }  // namespace phi
  