mxnet.initializer.Uniform¶

class mxnet.initializer.Uniform(scale=0.07)[source]¶

Initializes weights with random values uniformly sampled from a given range.

Parameters: scale (float, optional) – The bound on the range of the generated random values. Values are generated from the range [-scale, scale]. Default scale is 0.07.

Example

>>> # Given 'module', an instance of 'mxnet.module.Module', initialize weights
>>> # to random values uniformly sampled between -0.1 and 0.1.
...
>>> init = mx.init.Uniform(0.1)
>>> module.init_params(init)
>>> for dictionary in module.get_params():
...     for key in dictionary:
...         print(key)
...         print(dictionary[key].asnumpy())
...
fullyconnected0_weight
[[ 0.01360891 -0.02144304  0.08511933]]

__init__(scale=0.07)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

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