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FIX [bnb] Make unexpected_keys optional (#29420)

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* make `unexpected_keys` optional

* push

* Apply suggestions from code review

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
This commit is contained in:
Younes Belkada 2024-03-18 15:50:56 +01:00 committed by GitHub
parent 87e2ea33aa
commit c852d4fba6
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3 changed files with 9 additions and 7 deletions
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2
src/transformers/modeling_utils.py
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@ -3769,7 +3769,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
):
set_module_tensor_to_device(model, key, "cpu", value)
else:
hf_quantizer.create_quantized_param(model, value, key, "cpu", state_dict)
hf_quantizer.create_quantized_param(model, value, key, "cpu", state_dict, unexpected_keys)
# retrieve uninitialized modules and initialize before maybe overriding that with the pretrained weights.
if _fast_init:

7
src/transformers/quantizers/quantizer_bnb_4bit.py
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@ -12,7 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
from typing import TYPE_CHECKING, Any, Dict, List, Union
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
from packaging import version
@ -143,7 +143,7 @@ class Bnb4BitHfQuantizer(HfQuantizer):
param_name: str,
target_device: "torch.device",
state_dict: Dict[str, Any],
unexpected_keys: List[str],
unexpected_keys: Optional[List[str]] = None,
):
"""
combines logic from _load_state_dict_into_meta_model and .integrations.bitsandbytes.py::set_module_quantized_tensor_to_device()
@ -198,7 +198,8 @@ class Bnb4BitHfQuantizer(HfQuantizer):
for k, v in state_dict.items():
if param_name + "." in k:
quantized_stats[k] = v
unexpected_keys.remove(k)
if unexpected_keys is not None and k in unexpected_keys:
unexpected_keys.remove(k)
new_value = bnb.nn.Params4bit.from_prequantized(
data=param_value,

7
src/transformers/quantizers/quantizer_bnb_8bit.py
View File

@ -12,7 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
from typing import TYPE_CHECKING, Any, Dict, List, Union
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
from packaging import version
@ -162,7 +162,7 @@ class Bnb8BitHfQuantizer(HfQuantizer):
param_name: str,
target_device: "torch.device",
state_dict: Dict[str, Any],
unexpected_keys: List[str],
unexpected_keys: Optional[List[str]] = None,
):
"""
combines logic from _load_state_dict_into_meta_model and .integrations.bitsandbytes.py::set_module_quantized_tensor_to_device()
@ -207,7 +207,8 @@ class Bnb8BitHfQuantizer(HfQuantizer):
module._parameters[tensor_name] = new_value
if fp16_statistics is not None:
setattr(module.weight, "SCB", fp16_statistics.to(target_device))
unexpected_keys.remove(fp16_statistics_key)
if unexpected_keys is not None:
unexpected_keys.remove(fp16_statistics_key)
def _process_model_after_weight_loading(self, model: "PreTrainedModel", **kwargs):
model.is_loaded_in_8bit = True