chore: import upstream snapshot with attribution

python/paddle/sparse/multiary.py

@@ -0,0 +1,96 @@
+#   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.
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from paddle import _C_ops
+from paddle.base.framework import in_dynamic_or_pir_mode
+
+if TYPE_CHECKING:
+    from paddle import Tensor
+
+__all__ = []
+
+
+def addmm(
+    input: Tensor,
+    x: Tensor,
+    y: Tensor,
+    beta: float = 1.0,
+    alpha: float = 1.0,
+    name: str | None = None,
+) -> Tensor:
+    """
+    Applies matrix multiplication for `x` and `y` , `input` is added to
+    the final result. The equation is:
+
+    ..  math::
+
+        out = alpha * x * y + beta * input
+
+    The supported input/output Tensor layout are as follows:
+
+    Note:
+        input[SparseCsrTensor] + x[SparseCsrTensor] @ y[SparseCsrTensor] -> out[SparseCsrTensor]
+        input[DenseTensor] + x[SparseCsrTensor] @ y[DenseTensor] -> out[DenseTensor]
+        input[SparseCooTensor] + x[SparseCooTensor] @ y[SparseCooTensor] -> out[SparseCooTensor]
+        input[DenseTensor] + x[SparseCooTensor] @ y[DenseTensor] -> out[DenseTensor]
+
+    It supports backward propagation.
+
+    Dimensions `input` , `x` , `y` must be same and >= 2D. Automatic broadcasting of Tensor is not supported.
+
+    Args:
+        input (SparseTensor|DenseTensor): The input tensor. Shape is [*, M, N]. The data type can be float32 or float64.
+        x (SparseTensor): The input SparseTensor. Shape is [*, M, K]. The data type can be float32 or float64.
+        y (SparseTensor|DenseTensor): The input tensor. Shape is [*, K, N]. The data type can be float32 or float64.
+        beta (float, optional): Coefficient of `input` . Default: 1.0
+        alpha (float, optional): Coefficient of `x * y` . Default: 1.0
+        name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
+
+    Returns:
+        SparseTensor|DenseTensor: Tensor type, date type and shape is the same with `input` .
+
+    Examples:
+
+        .. code-block:: pycon
+
+            >>> # doctest: +REQUIRES(env:GPU)
+            >>> import paddle
+            >>> paddle.device.set_device('gpu')
+
+            >>> # dense + csr @ dense -> dense
+            >>> input = paddle.rand([3, 2])
+            >>> crows = [0, 1, 2, 3]
+            >>> cols = [1, 2, 0]
+            >>> values = [1.0, 2.0, 3.0]
+            >>> x = paddle.sparse.sparse_csr_tensor(crows, cols, values, [3, 3])
+            >>> y = paddle.rand([3, 2])
+            >>> out = paddle.sparse.addmm(input, x, y, 3.0, 2.0)
+
+            >>> # dense + coo @ dense -> dense
+            >>> input = paddle.rand([3, 2])
+            >>> indices = [[0, 1, 2], [1, 2, 0]]
+            >>> values = [1.0, 2.0, 3.0]
+            >>> x = paddle.sparse.sparse_coo_tensor(indices, values, [3, 3])
+            >>> y = paddle.rand([3, 2])
+            >>> out = paddle.sparse.addmm(input, x, y, 3.0, 2.0)
+
+    """
+    assert in_dynamic_or_pir_mode(), (
+        "Currently, Sparse API only support dynamic mode or pir mode."
+    )
+    return _C_ops.sparse_addmm(input, x, y, beta, alpha)