'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowercase          =  {
    '''configuration_electra''': ['''ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ElectraConfig''', '''ElectraOnnxConfig'''],
    '''tokenization_electra''': ['''ElectraTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  ['''ElectraTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''ElectraForCausalLM''',
						    '''ElectraForMaskedLM''',
						    '''ElectraForMultipleChoice''',
						    '''ElectraForPreTraining''',
						    '''ElectraForQuestionAnswering''',
						    '''ElectraForSequenceClassification''',
						    '''ElectraForTokenClassification''',
						    '''ElectraModel''',
						    '''ElectraPreTrainedModel''',
						    '''load_tf_weights_in_electra''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFElectraForMaskedLM''',
						    '''TFElectraForMultipleChoice''',
						    '''TFElectraForPreTraining''',
						    '''TFElectraForQuestionAnswering''',
						    '''TFElectraForSequenceClassification''',
						    '''TFElectraForTokenClassification''',
						    '''TFElectraModel''',
						    '''TFElectraPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''FlaxElectraForCausalLM''',
						    '''FlaxElectraForMaskedLM''',
						    '''FlaxElectraForMultipleChoice''',
						    '''FlaxElectraForPreTraining''',
						    '''FlaxElectraForQuestionAnswering''',
						    '''FlaxElectraForSequenceClassification''',
						    '''FlaxElectraForTokenClassification''',
						    '''FlaxElectraModel''',
						    '''FlaxElectraPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
						from .tokenization_electra import ElectraTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_electra_fast import ElectraTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_electra import (
												    ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ElectraForCausalLM,
												    ElectraForMaskedLM,
												    ElectraForMultipleChoice,
												    ElectraForPreTraining,
												    ElectraForQuestionAnswering,
												    ElectraForSequenceClassification,
												    ElectraForTokenClassification,
												    ElectraModel,
												    ElectraPreTrainedModel,
												    load_tf_weights_in_electra,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_electra import (
												    TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFElectraForMaskedLM,
												    TFElectraForMultipleChoice,
												    TFElectraForPreTraining,
												    TFElectraForQuestionAnswering,
												    TFElectraForSequenceClassification,
												    TFElectraForTokenClassification,
												    TFElectraModel,
												    TFElectraPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_electra import (
												    FlaxElectraForCausalLM,
												    FlaxElectraForMaskedLM,
												    FlaxElectraForMultipleChoice,
												    FlaxElectraForPreTraining,
												    FlaxElectraForQuestionAnswering,
												    FlaxElectraForSequenceClassification,
												    FlaxElectraForTokenClassification,
												    FlaxElectraModel,
												    FlaxElectraPreTrainedModel,
												)

else:
						import sys

						__lowercase          =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






from pathlib import Path

import fire






def    lowerCamelCase__				(				__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  int				):




			"""simple docstring"""


			lowerCAmelCase_						=	Path(__lowerCAmelCase				)
			lowerCAmelCase_						=	Path(__lowerCAmelCase				)
			dest_dir.mkdir(exist_ok=__lowerCAmelCase				)
			for path in src_dir.iterdir():
						lowerCAmelCase_						=	[x.rstrip() for x in list(path.open().readlines()				)][:n]
						lowerCAmelCase_						=	dest_dir.joinpath(path.name				)
						print(__lowerCAmelCase				)
						dest_path.open("w"				).write("\n".join(__lowerCAmelCase				)				)


if __name__ == "__main__":
			fire.Fire(minify)



