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Fix missing call in QuantizedTransformersModel #325

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Sep 30, 2024
Merged

Fix missing call in QuantizedTransformersModel #325

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eb281be
fix(transformers): add missing call implementation
dacorvo Sep 30, 2024
1a73135
feat(examples): use QuantizedModelForCausalLM
dacorvo Sep 30, 2024
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9 changes: 4 additions & 5 deletions examples/nlp/text-generation/quantize_causal_lm_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@
from datasets import load_dataset
from transformers import AutoModelForCausalLM, AutoTokenizer

from optimum.quanto import Calibration, freeze, qfloat8, qint4, qint8, quantize
from optimum.quanto import Calibration, QuantizedModelForCausalLM, qfloat8, qint4, qint8


@torch.no_grad()
Expand Down Expand Up @@ -133,15 +133,14 @@ def main():
print(f"{args.model} (w: {args.weights}, a: {args.activations})")
weights = keyword_to_itype(args.weights)
activations = keyword_to_itype(args.activations)
quantize(model, weights=weights, activations=activations)
qmodel = QuantizedModelForCausalLM.quantize(model, weights=weights, activations=activations)
if activations is not None:
print("Calibrating ...")
cal_dataset.shuffle(args.seed)
with Calibration(streamline=args.no_streamline, debug=args.debug):
cal_samples = args.batch_size * args.validation_batch
calibrate(model, tokenizer, cal_dataset, device, args.batch_size, samples=cal_samples)
freeze(model)
generate(model, tokenizer, device, args.prompt, args.max_new_tokens)
calibrate(qmodel, tokenizer, cal_dataset, device, args.batch_size, samples=cal_samples)
generate(qmodel, tokenizer, device, args.prompt, args.max_new_tokens)


if __name__ == "__main__":
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3 changes: 3 additions & 0 deletions optimum/quanto/models/transformers_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,9 @@ def __getattr__(self, name: str) -> Any:
def forward(self, *args, **kwargs):
return self._wrapped.forward(*args, **kwargs)

def __call__(self, *args, **kwargs):
return self._wrapped.forward(*args, **kwargs)

@staticmethod
def _qmap_name():
return f"{QuantizedTransformersModel.BASE_NAME}_qmap.json"
Expand Down
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