mindspore.ops.count_nonzero

mindspore.ops.count_nonzero(x, axis=(), keep_dims=False, dtype=mstype.int32)[source]

Count number of nonzero elements across axis of input tensor

Parameters

  • x (Tensor) – Input data is used to count non-zero numbers.

  • axis (Union[int, tuple(int), list(int)]) – The dimensions to reduce. Only constant value is allowed. Default: (), reduce all dimensions.

  • keep_dims (bool) – If true, keep these reduced dimensions and the length is 1. If false, don’t keep these dimensions. Default: False.

  • dtype (Union[Number, mstype.bool_]) – The data type of the output tensor. Only constant value is allowed. Default: mstype.int32

Returns

Tensor, number of nonzero element. The data type is dtype.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input_x = Tensor(np.array([[0, 1, 0], [1, 1, 0]]).astype(np.float32))
>>> nonzero_num = count_nonzero(x=input_x, axis=[0, 1], keep_dims=True, dtype=mstype.int32)
>>> print(nonzero_num)
[[3]]