mindspore.numpy.count_nonzero
- mindspore.numpy.count_nonzero(x, axis=None, keepdims=False)[source]
Counts the number of non-zero values in the tensor x.
- Parameters
x (Tensor) – The tensor for which to count non-zeros.
axis (Union[int,tuple], optional) – Axis or tuple of axes along which to count non-zeros. Default is None, meaning that non-zeros will be counted along a flattened version of x.
keepdims (bool, optional) – If this is set to True, the axes that are counted are left in the result as dimensions with size one. With this option, the result will broadcast correctly against x.
- Returns
Tensor, indicating number of non-zero values in the x along a given axis. Otherwise, the total number of non-zero values in x is returned.
- Raises
TypeError – If axis is not int or tuple.
ValueError – If axis is not in range [-x.ndim, x.ndim)
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore.numpy as np >>> x = np.asarray([1, 2, 3, -4, 0, 3, 2, 0]) >>> output = np.count_nonzero(x) >>> print(output) 6