I need a clarification of code written for some code in FastAI2 library.
this is the code WeightDropout written in FastAI2 library
class WeightDropout(Module):
“A module that warps another layer in which some weights will be replaced by 0 during training.”
def __init__(self, module, weight_p, layer_names='weight_hh_l0'):
self.module,self.weight_p,self.layer_names = module,weight_p,L(layer_names)
for layer in self.layer_names:
#Makes a copy of the weights of the selected layers.
w = getattr(self.module, layer)
delattr(self.module, layer)
self.register_parameter(f'{layer}_raw', nn.Parameter(w.data))
setattr(self.module, layer, F.dropout(w.data, p=self.weight_p, training=False))
if isinstance(self.module, (nn.RNNBase, nn.modules.rnn.RNNBase)):
self.module.flatten_parameters = self._do_nothing
def _setweights(self):
"Apply dropout to the raw weights."
for layer in self.layer_names:
raw_w = getattr(self, f'{layer}_raw')
setattr(self.module, layer, F.dropout(raw_w.data, p=self.weight_p, training=self.training))
def forward(self, *args):
self._setweights()
with warnings.catch_warnings():
#To avoid the warning that comes because the weights aren't flattened.
warnings.simplefilter("ignore")
return self.module.forward(*args)
def reset(self):
for layer in self.layer_names:
raw_w = getattr(self, f'{layer}_raw')
setattr(self.module, layer,
F.dropout(raw_w.data, p=self.weight_p, training=False))
if hasattr(self.module, 'reset'): self.module.reset()
def _do_nothing(self): pass
where above code randomly drops weights in weight matrix of hidden layers.I am primarily interested in ,
def _setweights(self):
"Apply dropout to the raw weights."
for layer in self.layer_names:
raw_w = getattr(self, f'{layer}_raw')
setattr(self.module, layer, F.dropout(raw_w.data, p=self.weight_p, training=self.training))
my question is that, does this operation of changing weights is recorded in gradient computation.