mindspore.mint.mul
- mindspore.mint.mul(input, other)[source]
Multiplies two tensors element-wise.
\[out_{i} = input_{i} * other_{i}\]Note
When the two inputs have different shapes, they must be able to broadcast to a common shape.
The two inputs can not be bool type at the same time, [True, Tensor(True, bool_), Tensor(np.array([True]), bool_)] are all considered bool type.
The two inputs comply with the implicit type conversion rules to make the data types consistent.
- Parameters
- Returns
Tensor, the shape is the same as the one after broadcasting, and the data type is the one with higher precision or higher digits among the two inputs.
- Raises
TypeError – If input and other is not one of the following: Tensor, number.Number, bool.
ValueError – If input and other are not the same shape.
- Supported Platforms:
Ascend
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, mint >>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) >>> y = Tensor(np.array([4.0, 5.0, 6.0]), mindspore.float32) >>> output = mint.mul(x, y) >>> print(output) [ 4. 10. 18.]