Package topo :: Package learningfn :: Module projfn :: Class CFPLF_PluginScaled

Class CFPLF_PluginScaled

CFPLearningFunction applying the specified single_cf_fn to each CF. Scales the single-connection learning rate by a scaling factor that is different for each individual unit. Thus each individual connection field uses a different learning rate.

Nested Classes

[hide private]

Inherited from param.parameterized.Parameterized: __metaclass__

Instance Methods

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__call__(self, iterator, input_activity, output_activity, learning_rate, **params)
Apply the specified single_cf_fn to every CF.

source code

update_scaling_factor(self, new_scaling_factor)
Update the single-connection learning rate scaling factor.

source code

Inherited from base.cf.CFPLearningFn: constant_sum_connection_rate

Inherited from param.parameterized.Parameterized: __getstate__, __init__, __repr__, __setstate__, __str__, debug, defaults, force_new_dynamic_value, get_param_values, get_value_generator, inspect_value, message, print_param_values, script_repr, set_default, set_dynamic_time_fn, set_param, state_pop, state_push, verbose, warning

Inherited from param.parameterized.Parameterized (private): _add_parameter, _instantiate_param, _set_name, _setup_params

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Class Methods

[hide private]

Inherited from param.parameterized.Parameterized: params, print_param_defaults

Class Variables

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learning_rate_scaling_factor = param.Parameter(default= None, ...
Matrix of scaling factors for scaling the learning rate of each CF individually.

name = <param.parameterized.String object at 0xb2875ec>
String identifier for this object.

single_cf_fn = param.ClassSelector(LearningFn, default= Hebbia...
Accepts a LearningFn that will be applied to each CF individually.

Inherited from param.parameterized.Parameterized: print_level

Properties

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Inherited from object: __class__

Method Details

[hide private]

call(self, iterator, input_activity, output_activity, learning_rate, **params)
(Call operator)

source code

Apply the specified single_cf_fn to every CF.

Overrides: base.cf.CFPLearningFn.__call__

Class Variable Details

[hide private]

learning_rate_scaling_factor

Matrix of scaling factors for scaling the learning rate of each CF individually.

Value:

param.Parameter(default= None, doc= "Matrix of scaling factors for scaling the lea
rning rate of each CF individually.")

single_cf_fn

Accepts a LearningFn that will be applied to each CF individually.

Value:

param.ClassSelector(LearningFn, default= Hebbian(), doc= "Accepts a LearningFn tha
t will be applied to each CF individually.")

Class CFPLF_PluginScaled

__call__(self, iterator, input_activity, output_activity, learning_rate, **params) (Call operator)

learning_rate_scaling_factor

single_cf_fn

call(self, iterator, input_activity, output_activity, learning_rate, **params)
(Call operator)