chore: import upstream snapshot with attribution
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// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <ATen/Functions.h>
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#include <ATen/core/TensorBody.h>
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#include <ATen/cuda/EmptyTensor.h>
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#include <ATen/native/cuda/Resize.h>
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#include <ATen/ops/tensor.h>
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#include <c10/core/Layout.h>
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#include <c10/core/ScalarType.h>
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#include <c10/core/SymInt.h>
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#include <c10/core/TensorOptions.h>
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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#include <c10/cuda/CUDAFunctions.h>
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#include <c10/cuda/CUDAGuard.h>
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#endif
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#include "ATen/ATen.h"
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#include "gtest/gtest.h"
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#include "paddle/phi/common/float16.h"
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#include "torch/all.h"
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TEST(TensorBaseTest, IsContiguousOrFalseAPI) {
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// Test with regular contiguous tensor
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at::Tensor contiguous_tensor = at::ones({2, 3, 4}, at::kFloat);
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ASSERT_TRUE(contiguous_tensor.is_contiguous_or_false());
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ASSERT_EQ(contiguous_tensor.is_contiguous_or_false(),
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contiguous_tensor.is_contiguous());
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// Test with view tensor (should still be contiguous if strides allow)
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at::TensorBase view_tensor = contiguous_tensor.view({6, 4});
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ASSERT_TRUE(view_tensor.is_contiguous_or_false());
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ASSERT_EQ(view_tensor.is_contiguous_or_false(), view_tensor.is_contiguous());
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// Test with different shapes
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at::TensorBase flat_tensor = at::ones({24}, at::kFloat);
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ASSERT_TRUE(flat_tensor.is_contiguous_or_false());
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at::TensorBase multi_dim_tensor = at::ones({2, 3, 4, 5}, at::kFloat);
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ASSERT_TRUE(multi_dim_tensor.is_contiguous_or_false());
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// Test with contiguous() method
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at::TensorBase made_contiguous = contiguous_tensor.contiguous();
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ASSERT_TRUE(made_contiguous.is_contiguous_or_false());
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// Test consistency between is_contiguous() and is_contiguous_or_false()
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// They should return the same value for all cases
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at::TensorBase tensor1 = at::ones({5, 6}, at::kDouble);
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ASSERT_EQ(tensor1.is_contiguous(), tensor1.is_contiguous_or_false());
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at::TensorBase tensor2 = at::ones({3, 4, 5}, at::kInt);
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ASSERT_EQ(tensor2.is_contiguous(), tensor2.is_contiguous_or_false());
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// Test with different dtypes
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at::TensorBase bool_tensor = at::ones({2, 3}, at::kBool);
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ASSERT_TRUE(bool_tensor.is_contiguous_or_false());
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at::TensorBase long_tensor = at::ones({2, 3}, at::kLong);
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ASSERT_TRUE(long_tensor.is_contiguous_or_false());
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}
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