mindspore.numpy.log

mindspore.numpy.log(x, dtype=None)[source]

Returns the natural logarithm, element-wise.

The natural logarithm log is the inverse of the exponential function, so that log(exp(x)) = x. The natural logarithm is logarithm in base e.

Note

Numpy arguments out, where, casting, order, subok, signature, and extobj are not supported. On GPU, the supported dtypes are np.float16, and np.float32. On CPU, the supported dtypes are np.float16, np.float32, and np.float64.

Parameters

x (Tensor) – Input array. For integer arguments with absolute value larger than 1 the result is always zero because of the way Python handles integer division. For integer zero the result is an overflow.
dtype (mindspore.dtype, optional) – defaults to None. Overrides the dtype of the output Tensor.

Returns

Tensor or scalar, the natural logarithm of x, element-wise. This is a scalar if x is a scalar.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> x = np.array([2, 3, 4]).astype('float32')
>>> output = np.log(x)
>>> print(output)
[0.69314575 1.09861    1.3862929 ]