Created
March 29, 2019 06:30
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| class CallbackHandler(): | |
| def __init__(self,cbs=None): | |
| self.cbs = cbs if cbs else [] | |
| def begin_fit(self, learn): | |
| self.learn,self.in_train = learn,True | |
| learn.stop = False | |
| res = True | |
| for cb in self.cbs: res = res and cb.begin_fit(learn) | |
| return res | |
| def after_fit(self): | |
| res = not self.in_train | |
| for cb in self.cbs: res = res and cb.after_fit() | |
| return res | |
| def begin_epoch(self, epoch): | |
| learn.model.train() | |
| self.in_train=True | |
| res = True | |
| for cb in self.cbs: res = res and cb.begin_epoch(epoch) | |
| return res | |
| def begin_validate(self): | |
| self.learn.model.eval() | |
| self.in_train=False | |
| res = True | |
| for cb in self.cbs: res = res and cb.begin_validate() | |
| return res | |
| def after_epoch(self): | |
| res = True | |
| for cb in self.cbs: res = res and cb.after_epoch() | |
| return res | |
| def begin_batch(self, xb, yb): | |
| res = True | |
| for cb in self.cbs: res = res and cb.begin_batch(xb, yb) | |
| return res | |
| def after_loss(self, loss): | |
| res = self.in_train | |
| for cb in self.cbs: res = res and cb.after_loss(loss) | |
| return res | |
| def after_backward(self): | |
| res = True | |
| for cb in self.cbs: res = res and cb.after_backward() | |
| return res | |
| def after_step(self): | |
| res = True | |
| for cb in self.cbs: res = res and cb.after_step() | |
| return res | |
| def do_stop(self): | |
| try: return learn.stop | |
| finally: learn.stop = False |
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