
import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


__a  			=					importlib.util.find_spec('s3fs') is not None

if _has_safs:
						from .safilesystem import SaFileSystem  # noqa: F401

__a  			=					[
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
						if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
												warnings.warn(f"A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.")
						fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)




def 				a						(							snake_case__:					Any					):


				'''simple docstring'''





				if "://" in dataset_path:
								lowercase_       =					dataset_path.split('''://'''					)[1]
				return dataset_path




def 				a						(							snake_case__:					str					):


				'''simple docstring'''





				if fs is not None and fs.protocol != "file":
								return True
				else:
								return False




def 				a						(							snake_case__:					Tuple						,   snake_case__:					Any						,   snake_case__:					Optional[Any]					):


				'''simple docstring'''
				lowercase_       =					not is_remote_filesystem(A_					)
				if is_local:
								# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
								shutil.move(fs._strip_protocol(A_					)						,   fs._strip_protocol(A_					)					)
				else:
								fs.mv(A_						,   A_						,   recursive=A_					)




def 				a						(							):


				'''simple docstring'''





				if hasattr(fsspec.asyn						,   '''reset_lock'''					):
								# for future fsspec>2022.05.0
								fsspec.asyn.reset_lock()
				else:
								lowercase_       =					None
								lowercase_       =					None
								lowercase_       =					threading.Lock()






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase			:     List[Any]           =   logging.get_logger(__name__)

__lowerCAmelCase			:     int           =   {
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}




class        UpperCAmelCase_			( _A     ):


  '''simple docstring'''







  a__           =		"""biogpt"""
  def __init__( self			: List[str]			,							UpperCamelCase__			: Optional[Any]=4_2384			,							UpperCamelCase__			: Union[str, Any]=1024			,							UpperCamelCase__			: Any=24			,							UpperCamelCase__			: Union[str, Any]=16			,							UpperCamelCase__			: Tuple=4096			,							UpperCamelCase__			: Tuple="gelu"			,							UpperCamelCase__			: Dict=0.1			,							UpperCamelCase__			: Dict=0.1			,							UpperCamelCase__			: str=1024			,							UpperCamelCase__			: Any=0.02			,							UpperCamelCase__			: List[str]=1E-12			,							UpperCamelCase__			: Dict=True			,							UpperCamelCase__			: Optional[int]=True			,							UpperCamelCase__			: Union[str, Any]=0.0			,							UpperCamelCase__			: Any=0.0			,							UpperCamelCase__			: List[str]=1			,							UpperCamelCase__			: Dict=0			,							UpperCamelCase__			: List[str]=2			,							**UpperCamelCase__			: Optional[int]			,							)			->	Tuple:







    """simple docstring"""






    __magic_name__				     =       vocab_size
    __magic_name__				     =       max_position_embeddings
    __magic_name__				     =       hidden_size
    __magic_name__				     =       num_hidden_layers
    __magic_name__				     =       num_attention_heads
    __magic_name__				     =       intermediate_size
    __magic_name__				     =       hidden_act
    __magic_name__				     =       hidden_dropout_prob
    __magic_name__				     =       attention_probs_dropout_prob
    __magic_name__				     =       initializer_range
    __magic_name__				     =       layer_norm_eps
    __magic_name__				     =       scale_embedding
    __magic_name__				     =       use_cache
    __magic_name__				     =       layerdrop
    __magic_name__				     =       activation_dropout
    super().__init__(pad_token_id=UpperCamelCase__			,							bos_token_id=UpperCamelCase__			,							eos_token_id=UpperCamelCase__			,							**UpperCamelCase__    )

