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@@ -55,7 +55,7 @@ class Trainer(T):
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self.setup_lr_schedule(
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lr=opts.learning_rate,
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lr_target=opts.lr_target,
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- lr_shift_trigger=(opts.lr_shift, "epochs"),
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+ lr_shift_trigger=(opts.lr_shift, "epoch"),
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lr_decrease_rate=opts.lr_decrease_rate,
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# needed for cosine annealing
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@@ -129,8 +129,9 @@ class Trainer(T):
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def setup_warm_up(self, epochs: int, after_warm_up_lr: float, warm_up_lr: float):
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- if epochs == 0:
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+ if epochs is None or epochs == 0:
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return
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+
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assert epochs > 0, "Warm-up argument must be positive!"
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self.offset = epochs
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