Skip to content

Fix bert issue #21963

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
gante merged 3 commits into from
Mar 6, 2023
Merged

Fix bert issue #21963

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
9da1cba
Fix gradient checkpointing bug Bert
Mar 1, 2023
0880d7a
run fix-copies after pip upgrade
Mar 6, 2023
7ba0b12
fix after run of fix-copies again
Mar 6, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 7 additions & 5 deletions src/transformers/models/align/modeling_align.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1077,6 +1077,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -1086,11 +1093,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/altclip/modeling_altclip.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -628,6 +628,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -637,11 +644,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/bert/modeling_bert.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -575,6 +575,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -584,11 +591,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/bert_generation/modeling_bert_generation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -385,6 +385,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -394,11 +401,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/bridgetower/modeling_bridgetower.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -760,6 +760,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -769,11 +776,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/camembert/modeling_camembert.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -506,6 +506,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -515,11 +522,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/chinese_clip/modeling_chinese_clip.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -891,6 +891,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -900,11 +907,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/clap/modeling_clap.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1578,6 +1578,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -1587,11 +1594,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/data2vec/modeling_data2vec_text.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -492,6 +492,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -501,11 +508,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/electra/modeling_electra.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -553,6 +553,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -562,11 +569,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/ernie/modeling_ernie.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -488,6 +488,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -497,11 +504,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/layoutlm/modeling_layoutlm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -469,6 +469,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -478,11 +485,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/markuplm/modeling_markuplm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -630,6 +630,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -639,11 +646,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/nezha/modeling_nezha.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -561,6 +561,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -570,11 +577,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

def create_custom_forward(module):
def custom_forward(*inputs):
Expand Down
12 changes: 7 additions & 5 deletions src/transformers/models/realm/modeling_realm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -568,6 +568,13 @@ def forward(
all_self_attentions = () if output_attentions else None
all_cross_attentions = () if output_attentions and self.config.add_cross_attention 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

next_decoder_cache = () if use_cache else None
for i, layer_module in enumerate(self.layer):
if output_hidden_states:
Expand All @@ -577,11 +584,6 @@ def forward(
past_key_value = past_key_values[i] if past_key_values is not None 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

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