Table Of Contents
Table Of Contents

Normal

class mxnet.initializer.Normal(sigma=0.01)[source]

Initializes weights with random values sampled from a normal distribution with a mean of zero and standard deviation of sigma.

Parameters:sigma (float, optional) – Standard deviation of the normal distribution. Default standard deviation is 0.01.

Example

>>> # Given 'module', an instance of 'mxnet.module.Module', initialize weights
>>> # to random values sampled from a normal distribution.
...
>>> init = mx.init.Normal(0.5)
>>> module.init_params(init)
>>> for dictionary in module.get_params():
...     for key in dictionary:
...         print(key)
...         print(dictionary[key].asnumpy())
...
fullyconnected0_weight
[[-0.3214761  -0.12660924  0.53789419]]
__init__(sigma=0.01)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([sigma]) Initialize self.
dumps() Saves the initializer to string
set_verbosity([verbose, print_func]) Switch on/off verbose mode