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One shot user flow tweaks #2195

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One shot user flow tweaks #2195

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48d617f
enable applying one shot to minilm (bert) model
robertgshaw2-redhat Mar 23, 2024
3196bea
cleanup
robertgshaw2-redhat Mar 23, 2024
95888f6
Update integration_helper_functions.py
robertgshaw2-redhat Mar 23, 2024
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2 changes: 1 addition & 1 deletion src/sparseml/transformers/finetune/data/custom.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
from sparseml.transformers.utils.preprocessing_functions import (
PreprocessingFunctionRegistry,
)
from sparsezoo.utils.helpers import import_from_path
# from sparsezoo.utils.helpers import import_from_path
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what is the issue here?

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If this was giving you issue might be a sparsezoo version issue



@TextGenerationDataset.register(name="custom", alias=["json", "csv"])
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5 changes: 4 additions & 1 deletion src/sparseml/transformers/finetune/runner.py
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Expand Up @@ -151,8 +151,11 @@ def one_shot(self, stage: Optional[str] = None):
"""
_LOGGER.info("*** One Shot ***")

tokenized_dataset = self.get_dataset_split("calibration")
if "labels" in tokenized_dataset.column_names:
tokenized_dataset = tokenized_dataset.remove_columns("labels")
Comment on lines +154 to +156
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what is the issue here? if this is relatively safe to keep, then leave a comment on why this specific column needs to be removed

calib_data = format_calibration_data(
tokenized_dataset=self.get_dataset_split("calibration"),
tokenized_dataset=tokenized_dataset,
num_calibration_samples=self._data_args.num_calibration_samples,
accelerator=self.trainer.accelerator,
)
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12 changes: 8 additions & 4 deletions src/sparseml/transformers/integration_helper_functions.py
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Expand Up @@ -144,10 +144,14 @@ def create_data_loader(
source_path = source_path or model.name_or_path
if tokenizer is None:
if sequence_length is None:
raise ValueError(
"Sequence length for the transformer model export missing. "
"Provide it manually using sequence_length argument"
)
if hasattr(model.config, "max_position_embeddings"):
sequence_length = model.config.max_position_embeddings
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Add a _LOGGER.info here that you are using the default and what the value is

else:
raise ValueError(
"Sequence length for the transformer model export missing and "
"could not detect using model.config.max_position_embeddings"
"Provide it manually using sequence_length argument"
)
tokenizer = initialize_tokenizer(config.name_or_path, sequence_length, task)
data_args = _parse_data_args(data_args or {})

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