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Fix gradient checkpointing bug in Speech2Text #22079

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Merged
gante merged 3 commits into from
Mar 10, 2023
Merged

Fix gradient checkpointing bug in Speech2Text #22079

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3d40e9b
Fix gradient checkpointing bug in Speech2Text
KMFODA Mar 10, 2023
543fbc5
Update modeling_speech_to_text.py
KMFODA Mar 10, 2023
0d05968
Update modeling_speech_to_text_2.py
KMFODA Mar 10, 2023
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13 changes: 7 additions & 6 deletions src/transformers/models/speech_to_text/modeling_speech_to_text.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1024,6 +1024,13 @@ def forward(
hidden_states = inputs_embeds + positions
hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=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

# decoder layers
all_hidden_states = () if output_hidden_states else None
all_self_attns = () if output_attentions else None
Expand All @@ -1048,12 +1055,6 @@ def forward(
past_key_value = past_key_values[idx] if past_key_values is not None else None

if self.gradient_checkpointing and self.training:
if use_cache:
logger.warning(
"`use_cache = True` is incompatible with gradient checkpointing. Setting `use_cache ="
" False`..."
)
use_cache = False

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
13 changes: 7 additions & 6 deletions src/transformers/models/speech_to_text_2/modeling_speech_to_text_2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -632,6 +632,13 @@ def forward(
hidden_states = inputs_embeds + positions
hidden_states = nn.functional.dropout(hidden_states, p=self.dropout, training=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

# decoder layers
all_hidden_states = () if output_hidden_states else None
all_self_attns = () if output_attentions else None
Expand All @@ -657,12 +664,6 @@ def forward(
past_key_value = past_key_values[idx] if past_key_values is not None else None

if self.gradient_checkpointing and self.training:
if use_cache:
logger.warning(
"`use_cache = True` is incompatible with gradient checkpointing. Setting `use_cache ="
" False`..."
)
use_cache = False

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down