2022-07-21 17:36:48 +08:00
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# Copyright (c) 2022 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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2024-07-10 14:38:34 +08:00
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from __future__ import annotations
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from typing import TYPE_CHECKING
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2022-10-12 10:32:54 +08:00
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from paddle import _C_ops
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2024-08-15 01:10:42 +08:00
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from paddle.base.framework import in_dynamic_or_pir_mode
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2024-07-10 14:38:34 +08:00
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if TYPE_CHECKING:
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from paddle import Tensor
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2022-07-21 17:36:48 +08:00
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__all__ = []
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2024-07-10 14:38:34 +08:00
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def addmm(
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input: Tensor,
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x: Tensor,
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y: Tensor,
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beta: float = 1.0,
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alpha: float = 1.0,
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name: str | None = None,
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) -> Tensor:
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"""
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Applies matrix multiplication for `x` and `y` , `input` is added to
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the final result. The equation is:
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.. math::
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2022-10-18 12:55:54 +08:00
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out = alpha * x * y + beta * input
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2022-09-14 21:56:19 +08:00
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2022-07-21 17:36:48 +08:00
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The supported input/output Tensor layout are as follows:
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2022-07-21 17:36:48 +08:00
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Note:
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input[SparseCsrTensor] + x[SparseCsrTensor] @ y[SparseCsrTensor] -> out[SparseCsrTensor]
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input[DenseTensor] + x[SparseCsrTensor] @ y[DenseTensor] -> out[DenseTensor]
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input[SparseCooTensor] + x[SparseCooTensor] @ y[SparseCooTensor] -> out[SparseCooTensor]
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input[DenseTensor] + x[SparseCooTensor] @ y[DenseTensor] -> out[DenseTensor]
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It supports backward propagation.
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Dimensions `input` , `x` , `y` must be same and >= 2D. Automatic broadcasting of Tensor is not supported.
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Args:
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input (SparseTensor|DenseTensor): The input tensor. Shape is [*, M, N]. The data type can be float32 or float64.
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x (SparseTensor): The input SparseTensor. Shape is [*, M, K]. The data type can be float32 or float64.
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y (SparseTensor|DenseTensor): The input tensor. Shape is [*, K, N]. The data type can be float32 or float64.
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beta (float, optional): Coefficient of `input` . Default: 1.0
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alpha (float, optional): Coefficient of `x * y` . Default: 1.0
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name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
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Returns:
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SparseTensor|DenseTensor: Tensor type, date type and shape is the same with `input` .
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Examples:
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2026-02-19 12:42:40 +08:00
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.. code-block:: pycon
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2022-07-21 17:36:48 +08:00
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2023-08-29 10:38:53 +08:00
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>>> # doctest: +REQUIRES(env:GPU)
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>>> import paddle
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>>> paddle.device.set_device('gpu')
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>>> # dense + csr @ dense -> dense
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>>> input = paddle.rand([3, 2])
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>>> crows = [0, 1, 2, 3]
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>>> cols = [1, 2, 0]
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>>> values = [1.0, 2.0, 3.0]
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>>> x = paddle.sparse.sparse_csr_tensor(crows, cols, values, [3, 3])
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>>> y = paddle.rand([3, 2])
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>>> out = paddle.sparse.addmm(input, x, y, 3.0, 2.0)
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>>> # dense + coo @ dense -> dense
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>>> input = paddle.rand([3, 2])
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>>> indices = [[0, 1, 2], [1, 2, 0]]
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>>> values = [1.0, 2.0, 3.0]
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>>> x = paddle.sparse.sparse_coo_tensor(indices, values, [3, 3])
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>>> y = paddle.rand([3, 2])
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>>> out = paddle.sparse.addmm(input, x, y, 3.0, 2.0)
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2022-09-14 21:56:19 +08:00
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2022-07-21 17:36:48 +08:00
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"""
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2025-08-21 02:07:41 +08:00
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assert in_dynamic_or_pir_mode(), (
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"Currently, Sparse API only support dynamic mode or pir mode."
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)
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2022-10-31 18:37:56 +08:00
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return _C_ops.sparse_addmm(input, x, y, beta, alpha)
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