




from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url


class  A		(  snake_case_     ):
		__snake_case									=   ''
		__snake_case									=   'hf-legacy'  # "hf://"" is reserved for hffs



		def __init__(     self,	UpperCamelCase__ = None,	UpperCamelCase__ = None,	**UpperCamelCase__,	):







								"""simple docstring"""



								super().__init__(self,	**UpperCamelCase__   )
								lowerCAmelCase_      			=  repo_info
								lowerCAmelCase_      			=  token
								lowerCAmelCase_      			=  None



		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								if self.dir_cache is None:
														lowerCAmelCase_      			=  {}
														for hf_file in self.repo_info.siblings:
																				# TODO(QL): add sizes
																				lowerCAmelCase_      			=  {
																				    '''name''': hf_file.rfilename,
																				    '''size''': None,
																				    '''type''': '''file''',
																				}
																				self.dir_cache.update(
																				    {
																				        str(UpperCamelCase__   ): {'''name''': str(UpperCamelCase__   ), '''size''': None, '''type''': '''directory'''}
																				        for d in list(PurePosixPath(hf_file.rfilename   ).parents   )[:-1]
																				    }   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = "rb",	**UpperCamelCase__,	):







								"""simple docstring"""



								if not isinstance(self.repo_info,	UpperCamelCase__   ):
														raise NotImplementedError(f"Open is only implemented for dataset repositories, but got {self.repo_info}"   )
								lowerCAmelCase_      			=  hf_hub_url(self.repo_info.id,	UpperCamelCase__,	revision=self.repo_info.sha   )
								return fsspec.open(
								    UpperCamelCase__,	mode=UpperCamelCase__,	headers=get_authentication_headers_for_url(UpperCamelCase__,	use_auth_token=self.token   ),	client_kwargs={'''trust_env''': True},	).open()



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	**UpperCamelCase__   ):







								"""simple docstring"""



								self._get_dirs()
								lowerCAmelCase_      			=  self._strip_protocol(UpperCamelCase__   )
								if path in self.dir_cache:
														return self.dir_cache[path]
								else:
														raise FileNotFoundError(UpperCamelCase__   )







		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__=False,	**UpperCamelCase__   ):







								"""simple docstring"""



								self._get_dirs()
								lowerCAmelCase_      			=  PurePosixPath(path.strip('''/'''   )   )
								lowerCAmelCase_      			=  {}
								for p, f in self.dir_cache.items():
														lowerCAmelCase_      			=  PurePosixPath(p.strip('''/'''   )   )
														lowerCAmelCase_      			=  p.parent
														if root == path:
																				lowerCAmelCase_      			=  f
								lowerCAmelCase_      			=  list(paths.values()   )
								if detail:
														return out
								else:
														return sorted(f['''name'''] for f in out   )












import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


lowercase  							=					logging.getLogger(__name__)




@dataclass
class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= field(
	    default=0.0       ,					metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''Whether to SortishSamler or not.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''whether to use adafactor'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''Dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default='''linear'''       ,					metadata={'''help''': F'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()				)}'''}       ,					)





