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Fix gradient checkpointing bug marian (#21842)
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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@ -995,6 +995,13 @@ class MarianDecoder(MarianPreTrainedModel):
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hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=self.training)
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if self.gradient_checkpointing and self.training:
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if use_cache:
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logger.warning_once(
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"`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
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)
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use_cache = False
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# decoder layers
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all_hidden_states = () if output_hidden_states else None
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all_self_attns = () if output_attentions else None
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@ -1019,11 +1026,6 @@ class MarianDecoder(MarianPreTrainedModel):
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past_key_value = past_key_values[idx] if past_key_values is not None else None
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if self.gradient_checkpointing and self.training:
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if use_cache:
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logger.warning_once(
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"`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
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)
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use_cache = False
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def create_custom_forward(module):
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def custom_forward(*inputs):
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