mindspore.mint.add
- mindspore.mint.add(input, other, *, alpha=1)[source]
Adds scaled other value to input Tensor.
\[out_{i} = input_{i} + alpha \times other_{i}\]Note
When the two inputs have different shapes, they must be able to broadcast to a common shape.
The two inputs and alpha comply with the implicit type conversion rules to make the data types consistent.
- Parameters
- Keyword Arguments
alpha (number.Number) – A scaling factor applied to other, default 1.
- Returns
Tensor with a shape that is the same as the broadcasted shape of the input input and other, and the data type is the one with higher precision or higher digits among the two inputs and alpha.
- Raises
- Supported Platforms:
Ascend
Examples
>>> import numpy as np >>> import mindspore >>> from mindspore import Tensor >>> from mindspore import mint >>> x = Tensor(1, mindspore.int32) >>> y = Tensor(np.array([4, 5, 6]).astype(np.float32)) >>> alpha = 0.5 >>> output = mint.add(x, y, alpha=alpha) >>> print(output) [3. 3.5 4.] >>> # the data type of x is int32, the data type of y is float32, >>> # alpha is a float, and the output is the data format of higher precision float32. >>> print(output.dtype) Float32