from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from caffe2.python.modeling.parameter_info import ParameterInfo class Initializer(object): ''' This class abstracts out parameter creation. One can come up with a new Initializer in order to implement more complex parameter initializaion logic ''' def __init__(self, operator_name=None, **kwargs): self.operator_name = operator_name self.operator_kwargs = kwargs def update(self, operator_name, kwargs): if self.operator_name is not None: raise Exception("Operator name overwrites are not allowed") self.operator_name = operator_name self.operator_kwargs = kwargs def create_param(self, param_name, init_net, shape): param = init_net.__getattr__(self.operator_name)( [], param_name, shape=shape, **self.operator_kwargs) return ParameterInfo( param_id=None, param=param, shape=shape, ) def update_initializer(initializer_class, operator_name_and_kwargs, default_operator_name_and_kwargs): ''' A helper function to convert from operator_name_and_kwargs to new object of type initializer_class. This function serves two purposes: 1. Support for custom initialization operators being passed in 2. Allow user to specify a custom Initializer without overwriting default operators used for initialization If initializer_class is None, creates a default initializer using the Initializer class and operator_name_and_kwargs provided If operator_name_and_kwargs is None, uses default_operator_name_and_kwargs returns an instantiated Initializer object ''' def get_initializer_args(): return ( operator_name_and_kwargs or default_operator_name_and_kwargs ) if initializer_class is not None: init = initializer_class(get_initializer_args()[0], **get_initializer_args()[1]) else: init = Initializer( get_initializer_args()[0], **get_initializer_args()[1] ) return init