def normal(shape,
dtype=default_override_or(np.float32),
mean=0.0,
scale=1.0,
seed=auto_select,
name=''):
"""normal(shape, dtype=default_override_or(np.float32), mean=0.0, scale=1.0, seed=auto_select, name='')
Generates samples from the normal distribution with mean `mean` and standard deviation `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.
mean (float): mean of the distribution
scale (float): scale (standard deviation) 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:
>>> z = C.random.normal((2,3), seed=98052)
>>> z.eval(device=C.cpu()) # explicitly setting cpu because this is tested on multiple platforms; leave it unspecified in your code
array([[ 1.803254, 0.995395, -0.631974],
[-1.73672 , 0.005615, -0.340025]], dtype=float32)
"""
from cntk.cntk_py import normal_random
shape, dtype = sanitize_random_args(shape, dtype)
return normal_random(shape, dtype, mean, scale, seed, name)
def normal(shape, dtype=default_override_or(np.float32), mean=0.0, scale=1.0, seed=auto_select, name=''):
"""normal(shape, dtype=default_override_or(np.float32), mean=0.0, scale=1.0, seed=auto_select, name='')
Generates samples from the normal distribution with mean `mean` and standard deviation `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.
mean (float): mean of the distribution
scale (float): scale (standard deviation) 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:
>>> z = C.random.normal((2,3), seed=98052)
>>> z.eval(device=C.cpu()) # explicitly setting cpu because this is tested on multiple platforms; leave it unspecified in your code
array([[ 1.803254, 0.995395, -0.631974],
[-1.73672 , 0.005615, -0.340025]], dtype=float32)
"""
from cntk.cntk_py import normal_random
shape, dtype = sanitize_random_args(shape, dtype)
return normal_random(shape, dtype, mean, scale, seed, name)