added warning
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@@ -159,8 +159,8 @@ class BertAdam(Optimizer):
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# warning for exceeding t_total (only active with warmup_linear
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# warning for exceeding t_total (only active with warmup_linear
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if group['schedule'] == "warmup_linear" and progress > 1. and not warned_for_t_total:
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if group['schedule'] == "warmup_linear" and progress > 1. and not warned_for_t_total:
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logger.warning(
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logger.warning(
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"Training beyond specified 't_total' steps. Learning rate set to {}. "
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"Training beyond specified 't_total' steps with schedule '{}'. Learning rate set to {}. "
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"Please set 't_total' of {} correctly.".format(lr_scheduled, self.__class__.__name__))
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"Please set 't_total' of {} correctly.".format(group['schedule'], lr_scheduled, self.__class__.__name__))
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warned_for_t_total = True
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warned_for_t_total = True
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# end warning
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# end warning
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else:
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else:
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@@ -29,14 +29,14 @@ def warmup_cosine(x, warmup=0.002):
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return 0.5 * (1.0 + torch.cos(math.pi * x))
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return 0.5 * (1.0 + torch.cos(math.pi * x))
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def warmup_constant(x, warmup=0.002):
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def warmup_constant(x, warmup=0.002):
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""" Linearly increases learning rate over `warmup`*`t_total` (as provided to BertAdam) training steps.
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""" Linearly increases learning rate over `warmup`*`t_total` (as provided to OpenAIAdam) training steps.
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Learning rate is 1. afterwards. """
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Learning rate is 1. afterwards. """
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if x < warmup:
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if x < warmup:
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return x/warmup
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return x/warmup
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return 1.0
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return 1.0
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def warmup_linear(x, warmup=0.002):
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def warmup_linear(x, warmup=0.002):
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""" Specifies a triangular learning rate schedule where peak is reached at `warmup`*`t_total`-th (as provided to BertAdam) training step.
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""" Specifies a triangular learning rate schedule where peak is reached at `warmup`*`t_total`-th (as provided to OpenAIAdam) training step.
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After `t_total`-th training step, learning rate is zero. """
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After `t_total`-th training step, learning rate is zero. """
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if x < warmup:
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if x < warmup:
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return x/warmup
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return x/warmup
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@@ -142,8 +142,8 @@ class OpenAIAdam(Optimizer):
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# warning for exceeding t_total (only active with warmup_linear
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# warning for exceeding t_total (only active with warmup_linear
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if group['schedule'] == "warmup_linear" and progress > 1. and not warned_for_t_total:
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if group['schedule'] == "warmup_linear" and progress > 1. and not warned_for_t_total:
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logger.warning(
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logger.warning(
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"Training beyond specified 't_total' steps. Learning rate set to {}. "
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"Training beyond specified 't_total' steps with schedule '{}'. Learning rate set to {}. "
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"Please set 't_total' of {} correctly.".format(lr_scheduled, self.__class__.__name__))
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"Please set 't_total' of {} correctly.".format(group['schedule'], lr_scheduled, self.__class__.__name__))
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warned_for_t_total = True
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warned_for_t_total = True
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# end warning
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# end warning
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else:
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else:
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