chore: import upstream snapshot with attribution

test/cpp/phi/common/test_int_array.cc

@@ -0,0 +1,154 @@
+/* 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 "gtest/gtest.h"
+#include "paddle/phi/api/include/api.h"
+#include "paddle/phi/api/include/context_pool.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/common/int_array.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/full_kernel.h"
+
+PD_DECLARE_KERNEL(full, CPU, ALL_LAYOUT);
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
+PD_DECLARE_KERNEL(full, GPU, ALL_LAYOUT);
+#endif
+
+namespace phi {
+namespace tests {
+
+TEST(IntArray, ConstructFromCPUDenseTensor) {
+  auto& pool = paddle::experimental::DeviceContextPool::Instance();
+  const auto* dev_ctx = static_cast<const CPUContext*>(pool.Get(CPUPlace()));
+  DenseTensor shape = Full<int>(*dev_ctx, {2}, 3);
+  DenseTensor out = Full<int>(*dev_ctx, shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromCPUDenseTensorVector) {
+  auto& pool = paddle::experimental::DeviceContextPool::Instance();
+  const auto* dev_ctx = static_cast<const CPUContext*>(pool.Get(CPUPlace()));
+  DenseTensor shape0 = Full<int>(*dev_ctx, {1}, 3);
+  DenseTensor shape1 = Full<int64_t>(*dev_ctx, {1}, 3);
+  std::vector<DenseTensor> shape{shape0, shape1};
+  DenseTensor out = Full<int>(*dev_ctx, shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromCPUTensor) {
+  auto shape = paddle::experimental::full({2}, 3, DataType::INT64);
+  auto out = paddle::experimental::full(shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromCPUTensorVector) {
+  auto shape0 = paddle::experimental::full({2}, 3, DataType::INT64);
+  auto shape1 = paddle::experimental::full({2}, 3, DataType::INT32);
+
+  std::vector<paddle::Tensor> shape{shape0, shape0};
+  auto out = paddle::experimental::full(shape, 1);
+
+  std::vector<paddle::Tensor> shape_new{shape0, shape1};
+  auto out1 = paddle::experimental::full(shape_new, 1);
+
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+
+  ASSERT_EQ(out1.dims().size(), 2);
+  ASSERT_EQ(out1.dims()[0], 3);
+  ASSERT_EQ(out1.dims()[1], 3);
+  ASSERT_EQ(out1.numel(), 9);
+}
+
+TEST(IntArray, ThrowException) {
+  auto shape = paddle::experimental::full({2}, 3, DataType::FLOAT32);
+  auto create_int_array = [&shape]() -> paddle::experimental::IntArray {
+    paddle::experimental::IntArray int_array{shape};
+    return int_array;
+  };
+  ASSERT_ANY_THROW(create_int_array());
+}
+
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
+TEST(IntArray, ConstructFromGPUDenseTensor) {
+  auto& pool = paddle::experimental::DeviceContextPool::Instance();
+  const auto* dev_ctx =
+      static_cast<const phi::GPUContext*>(pool.Get(GPUPlace()));
+  DenseTensor shape = Full<int>(*dev_ctx, {2}, 3);
+  DenseTensor out = Full<int>(*dev_ctx, shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromGPUDenseTensorVector) {
+  auto& pool = paddle::experimental::DeviceContextPool::Instance();
+  const auto* dev_ctx =
+      static_cast<const phi::GPUContext*>(pool.Get(GPUPlace()));
+  DenseTensor shape0 = Full<int>(*dev_ctx, {1}, 3);
+  DenseTensor shape1 = Full<int64_t>(*dev_ctx, {1}, 3);
+  std::vector<DenseTensor> shape{shape0, shape1};
+  DenseTensor out = Full<int>(*dev_ctx, shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromGPUTensor) {
+  auto shape = paddle::experimental::full({2}, 3, DataType::INT64, GPUPlace());
+  auto out = paddle::experimental::full(shape, 1);
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+}
+
+TEST(IntArray, ConstructFromGPUTensorVector) {
+  auto shape0 = paddle::experimental::full({2}, 3, DataType::INT64, GPUPlace());
+  auto shape1 = paddle::experimental::full({2}, 3, DataType::INT32, GPUPlace());
+
+  std::vector<paddle::Tensor> shape{shape0, shape0};
+  auto out = paddle::experimental::full(shape, 1);
+
+  std::vector<paddle::Tensor> shape_new{shape0, shape1};
+  auto out1 = paddle::experimental::full(shape_new, 1);
+
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+
+  ASSERT_EQ(out1.dims().size(), 2);
+  ASSERT_EQ(out1.dims()[0], 3);
+  ASSERT_EQ(out1.dims()[1], 3);
+  ASSERT_EQ(out1.numel(), 9);
+}
+#endif
+
+}  // namespace tests
+}  // namespace phi