clean up optimizer from unused functions

optimization.py

@@ -90,27 +90,6 @@ def get_lr(self):
                 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.