mindspore.mint.mv

mindspore.mint.mv(input, vec)

Multiply matrix input and vector vec. If input is a tensor with shape \((N, M)\) and vec is a tensor with shape \((M,)\), The output is a 1-D tensor which shape is \((N,)\).

Warning

This is an experimental API that is subject to change or deletion.

Parameters

• input (Tensor) – The input matrix which shape is \((N,M)\) and the rank must be 2-D.

• vec (Tensor) – The input vector which shape is \((M,)\) and the rank is 1-D.

Returns

Tensor, the shape is \((N,)\).

Raises

• TypeError – If input or vec is not a tensor.

• TypeError – If the dtype of input or vec is not float16 or float32.

• TypeError – If the dtypes of input and vec are different.

• ValueError – If the input is not a 2-D tensor or the vec is not a 1-D tensor.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> input = Tensor(np.array([[3., 4.], [1., 6.], [1., 3.]]).astype(np.float32))
>>> vec = Tensor(np.array([1., 2.]).astype(np.float32))
>>> output = mint.mv(input, vec)
>>> print(output)
[11. 13. 7.]