chore: import upstream snapshot with attribution

paddle/phi/api/include/compat/ATen/ops/tensor.h

@@ -0,0 +1,47 @@
+// Copyright (c) 2025 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.
+
+// The file has been adapted from pytorch project
+// Licensed under BSD-style license -
+// https://github.com/pytorch/pytorch/blob/main/LICENSE
+
+#pragma once
+#include <ATen/core/Tensor.h>
+#include <c10/core/ScalarType.h>
+
+#include "paddle/common/macros.h"
+
+namespace at {
+
+#define TENSOR(T, S)                                                          \
+  PADDLE_API Tensor tensor(ArrayRef<T> values, const TensorOptions& options); \
+  inline Tensor tensor(std::initializer_list<T> values,                       \
+                       const TensorOptions& options) {                        \
+    return at::tensor(ArrayRef<T>(values), options);                          \
+  }                                                                           \
+  inline Tensor tensor(T value, const TensorOptions& options) {               \
+    return at::tensor(ArrayRef<T>(value), options);                           \
+  }                                                                           \
+  inline Tensor tensor(ArrayRef<T> values) {                                  \
+    return at::tensor(std::move(values), at::dtype(k##S));                    \
+  }                                                                           \
+  inline Tensor tensor(std::initializer_list<T> values) {                     \
+    return at::tensor(ArrayRef<T>(values));                                   \
+  }                                                                           \
+  inline Tensor tensor(T value) { return at::tensor(ArrayRef<T>(value)); }
+AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, TENSOR)
+AT_FORALL_COMPLEX_TYPES(TENSOR)
+#undef TENSOR
+
+}  // namespace at