Pass datasets trust_remote_code (#31406)
* Pass datasets trust_remote_code * Pass trust_remote_code in more tests * Add trust_remote_dataset_code arg to some tests * Revert "Temporarily pin datasets upper version to fix CI" This reverts commitb7672826ca. * Pass trust_remote_code in librispeech_asr_dummy docstrings * Revert "Pin datasets<2.20.0 for examples" This reverts commit833fc17a3e. * Pass trust_remote_code to all examples * Revert "Add trust_remote_dataset_code arg to some tests" to research_projects * Pass trust_remote_code to tests * Pass trust_remote_code to docstrings * Fix flax examples tests requirements * Pass trust_remote_dataset_code arg to tests * Replace trust_remote_dataset_code with trust_remote_code in one example * Fix duplicate trust_remote_code * Replace args.trust_remote_dataset_code with args.trust_remote_code * Replace trust_remote_dataset_code with trust_remote_code in parser * Replace trust_remote_dataset_code with trust_remote_code in dataclasses * Replace trust_remote_dataset_code with trust_remote_code arg
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@@ -136,6 +136,16 @@ class DataTrainingArguments:
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dataset_config_name: Optional[str] = field(
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default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
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)
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trust_remote_code: bool = field(
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default=False,
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metadata={
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"help": (
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"Whether to trust the execution of code from datasets/models defined on the Hub."
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" This option should only be set to `True` for repositories you trust and in which you have read the"
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" code, as it will execute code present on the Hub on your local machine."
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)
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},
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)
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text_column: Optional[str] = field(
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default=None,
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metadata={"help": "The name of the column in the datasets containing the full texts (for summarization)."},
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@@ -442,6 +452,7 @@ def main():
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cache_dir=data_args.dataset_cache_dir,
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num_proc=data_args.preprocessing_num_workers,
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token=True if model_args.use_auth_token else None,
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trust_remote_code=data_args.trust_remote_code,
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)
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if training_args.do_eval:
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@@ -452,6 +463,7 @@ def main():
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cache_dir=data_args.dataset_cache_dir,
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num_proc=data_args.preprocessing_num_workers,
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token=True if model_args.use_auth_token else None,
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trust_remote_code=data_args.trust_remote_code,
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)
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if not training_args.do_train and not training_args.do_eval:
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