clean up optimizer from unused functions

This commit is contained in:
thomwolf
2018-11-09 11:23:55 +01:00
parent 34a1a01091
commit 9e95cd8cd6

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@@ -90,27 +90,6 @@ class BERTAdam(Optimizer):
lr.append(lr_scheduled)
return lr
def to(self, device):
""" Move the optimizer state to a specified device"""
for state in self.state.values():
state['exp_avg'].to(device)
state['exp_avg_sq'].to(device)
def initialize_step(self, initial_step):
"""Initialize state with a defined step (but we don't have stored averaged).
Arguments:
initial_step (int): Initial step number.
"""
for group in self.param_groups:
for p in group['params']:
state = self.state[p]
# State initialization
state['step'] = initial_step
# Exponential moving average of gradient values
state['exp_avg'] = torch.zeros_like(p.data)
# Exponential moving average of squared gradient values
state['exp_avg_sq'] = torch.zeros_like(p.data)
def step(self, closure=None):
"""Performs a single optimization step.