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[Generate] Fix gradient_checkpointing and use_cache bug for BLOOM (#21956)

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Step 1 - Change use_cache fix
This commit is contained in:
Srimanth Agastyaraju 2023-03-06 09:56:40 -05:00 committed by GitHub
parent 934d0b8bdd
commit f3c75f8b44
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1 changed files with 7 additions and 5 deletions
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src/transformers/models/bloom/modeling_bloom.py
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@ -732,6 +732,13 @@ class BloomModel(BloomPreTrainedModel):
all_self_attentions = () if output_attentions else None all_self_attentions = () if output_attentions else None
all_hidden_states = () if output_hidden_states else None all_hidden_states = () if output_hidden_states else None
if self.gradient_checkpointing and self.training:
if use_cache:
logger.warning_once(
"`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
)
use_cache = False
# Compute alibi tensor: check build_alibi_tensor documentation # Compute alibi tensor: check build_alibi_tensor documentation
seq_length_with_past = seq_length seq_length_with_past = seq_length
past_key_values_length = 0 past_key_values_length = 0
@ -756,11 +763,6 @@ class BloomModel(BloomPreTrainedModel):
all_hidden_states = all_hidden_states + (hidden_states,) all_hidden_states = all_hidden_states + (hidden_states,)
if self.gradient_checkpointing and self.training: if self.gradient_checkpointing and self.training:
if use_cache:
logger.warning_once(
"`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`..."
)
use_cache = False
def create_custom_forward(module): def create_custom_forward(module):
def custom_forward(*inputs): def custom_forward(*inputs):