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