def gumbel(shape, dtype=default_override_or(np.float32), loc=0.0, scale=1.0, seed=auto_select, name=''):
"""gumbel(shape, dtype=default_override_or(np.float32), loc=0.0, scale=1.0, seed=auto_select, name='')
Generates samples from the Gumbel distribution with location `loc` and scale `scale`.
Args:
shape (tuple): shape of the output (entries are independent random draws)
dtype (np.float32 or np.float64): data type. Default is np.float32.
loc (float): location of the distribution
scale (float): scale of the distribution
seed (int): pseudo random number generator seed (default: automatically select a unique seed)
name (str, optional): the name of the Function instance in the network
Returns:
:class:`~cntk.ops.functions.Function`
Examples:
>>> g = C.random.gumbel((2,3), seed=98052)
>>> g.eval(device=C.cpu()) # explicitly setting cpu because this is tested on multiple platforms; leave it unspecified in your code
array([[-0.987713, -0.522298, 0.425918],
[-1.019599, 5.435177, 1.586071]], dtype=float32)
See also:
`The Gumbel-Max Trick
<https://hips.seas.harvard.edu/blog/2013/04/06/the-gumbel-max-trick-for-discrete-distributions/>`_.
"""
from cntk.cntk_py import gumbel_random
shape, dtype = sanitize_random_args(shape, dtype)
return gumbel_random(shape, dtype, loc, scale, seed, name)
def gumbel(shape,
dtype=default_override_or(np.float32),
loc=0.0,
scale=1.0,
seed=auto_select,
name=''):
"""gumbel(shape, dtype=default_override_or(np.float32), loc=0.0, scale=1.0, seed=auto_select, name='')
Generates samples from the Gumbel distribution with location `loc` and scale `scale`.
Args:
shape (tuple): shape of the output (entries are independent random draws)
dtype (np.float32 or np.float64): data type. Default is np.float32.
loc (float): location of the distribution
scale (float): scale of the distribution
seed (int): pseudo random number generator seed (default: automatically select a unique seed)
name (str, optional): the name of the Function instance in the network
Returns:
:class:`~cntk.ops.functions.Function`
Examples:
>>> g = C.random.gumbel((2,3), seed=98052)
>>> g.eval(device=C.cpu()) # explicitly setting cpu because this is tested on multiple platforms; leave it unspecified in your code
array([[-0.987713, -0.522298, 0.425918],
[-1.019599, 5.435177, 1.586071]], dtype=float32)
See also:
`The Gumbel-Max Trick
<https://hips.seas.harvard.edu/blog/2013/04/06/the-gumbel-max-trick-for-discrete-distributions/>`_.
"""
from cntk.cntk_py import gumbel_random
shape, dtype = sanitize_random_args(shape, dtype)
return gumbel_random(shape, dtype, loc, scale, seed, name)