mxnet.np.zeros_like¶
-
zeros_like
(a, dtype=None, order='C', device=None, out=None)¶ Return an array of zeros with the same shape and type as a given array.
- Parameters
a (ndarray) – The shape and data-type of a define these same attributes of the returned array.
dtype (data-type, optional) – Overrides the data type of the result. Temporarily do not support boolean type.
order ({'C'}, optional) – Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory. Currently only supports C order.
device (Device, optional) – Device context on which the memory is allocated. Default is mxnet.device.current_device().
out (ndarray or None, optional) – A location into which the result is stored. If provided, it must have the same shape and dtype as input ndarray. If not provided or None, a freshly-allocated array is returned.
- Returns
out – Array of zeros with the same shape and type as a.
- Return type
ndarray
See also
empty_like()
Return an empty array with shape and type of input.
ones_like()
Return an array of ones with shape and type of input.
zeros_like()
Return an array of zeros with shape and type of input.
full()
Return a new array of given shape filled with value.
Examples
>>> x = np.arange(6) >>> x = x.reshape((2, 3)) >>> x array([[0., 1., 2.], [3., 4., 5.]]) >>> np.zeros_like(x) array([[0., 0., 0.], [0., 0., 0.]]) >>> np.zeros_like(x, int) array([[0, 0, 0], [0, 0, 0]], dtype=int64) >>> y = np.arange(3, dtype=float) >>> y array([0., 1., 2.], dtype=float64) >>> np.zeros_like(y) array([0., 0., 0.], dtype=float64)