mars.tensor.random.standard_normal#

mars.tensor.random.standard_normal(size=None, chunk_size=None, gpu=None, dtype=None)[source]#

Draw samples from a standard Normal distribution (mean=0, stdev=1).

Parameters

  • size (int or tuple of ints, optional) – Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.

  • chunk_size (int or tuple of int or tuple of ints, optional) – Desired chunk size on each dimension

  • gpu (bool, optional) – Allocate the tensor on GPU if True, False as default

  • dtype (data-type, optional) – Data-type of the returned tensor.

Returns

out – Drawn samples.

Return type

float or Tensor

Examples

>>> import mars.tensor as mt

>>> s = mt.random.standard_normal(8000)
>>> s.execute()
array([ 0.6888893 ,  0.78096262, -0.89086505, ...,  0.49876311, #random
       -0.38672696, -0.4685006 ])                               #random
>>> s.shape
(8000,)
>>> s = mt.random.standard_normal(size=(3, 4, 2))
>>> s.shape
(3, 4, 2)