mindspore.mint.log2

mindspore.mint.log2(input)[source]

Returns the logarithm to the base 2 of a tensor element-wise.

\[y_i = \log_2(x_i)\]

Warning

If the input value of operator Log2 is within the range (0, 0.01] or [0.95, 1.05], the output accuracy may be affacted.

Parameters: input (Tensor) – Input Tensor of any dimension. The value must be greater than 0.
Returns: Tensor, has the same shape as the input. If input.dtype is of integer or boolean type, the output dtype will be float32. Otherwise, the output dtype will be the same as input.dtype.
Raises: TypeError – If input is not a Tensor.

Supported Platforms:: Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> x = Tensor(np.array([3.0, 5.0, 7.0]), mindspore.float32)
>>> output = mint.log2(x)
>>> print(output)
[1.5849625 2.321928  2.807355 ]