mars.tensor.zeros_like#

mars.tensor.zeros_like(a, dtype=None, gpu=None, order='K')[source]#

Return a tensor of zeros with the same shape and type as a given tensor.

Parameters

  • a (array_like) – 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.

  • gpu (bool, optional) – Allocate the tensor on GPU if True, None as default

  • order ({'C', 'F', 'A', or 'K'}, optional) – Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible.

Returns

out – tensor of zeros with the same shape and type as a.

Return type

Tensor

See also

ones_like

Return an array of ones with shape and type of input.

empty_like

Return an empty array with shape and type of input.

zeros

Return a new array setting values to zero.

ones

Return a new array setting values to one.

empty

Return a new uninitialized array.

Examples

>>> import mars.tensr as mt
>>> x = mt.arange(6)
>>> x = x.reshape((2, 3))
>>> x.execute()
array([[0, 1, 2],
       [3, 4, 5]])

>>> mt.zeros_like(x).execute()
array([[0, 0, 0],
       [0, 0, 0]])

>>> y = mt.arange(3, dtype=float)
>>> y.execute()
array([ 0.,  1.,  2.])

>>> mt.zeros_like(y).execute()
array([ 0.,  0.,  0.])