
import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader





class     lowerCamelCase      (       __lowerCamelCase					):







	def __init__(     self      :List[str]   ,     lowercase      :NestedDataStructureLike[PathLike]   ,     lowercase      :Optional[NamedSplit] = None   ,     lowercase      :Optional[Features] = None   ,     lowercase      :str = None   ,     lowercase      :bool = False   ,     lowercase      :bool = False   ,     lowercase      :Optional[str] = None   ,     lowercase      :Optional[int] = None   ,     **lowercase      :Any   ,     )		->      Optional[int]:







				"""simple docstring"""






				super().__init__(
				    lowercase   ,     split=lowercase   ,     features=lowercase   ,     cache_dir=lowercase   ,     keep_in_memory=lowercase   ,     streaming=lowercase   ,     num_proc=lowercase   ,     **lowercase   ,     )
				SCREAMING_SNAKE_CASE     						= field
				SCREAMING_SNAKE_CASE     						= path_or_paths if isinstance(lowercase   ,     lowercase			) else {self.split: path_or_paths}
				SCREAMING_SNAKE_CASE     						= Json(
				    cache_dir=lowercase   ,     data_files=lowercase   ,     features=lowercase   ,     field=lowercase   ,     **lowercase   ,     )







	def  snake_case__     (     self      :Union[str, Any]			)		->      Any:







				"""simple docstring"""






				if self.streaming:
							SCREAMING_SNAKE_CASE     						= self.builder.as_streaming_dataset(split=self.split			)
				# Build regular (map-style) dataset
				else:
							SCREAMING_SNAKE_CASE     						= None
							SCREAMING_SNAKE_CASE     						= None
							SCREAMING_SNAKE_CASE     						= None
							SCREAMING_SNAKE_CASE     						= None

							self.builder.download_and_prepare(
							    download_config=lowercase   ,     download_mode=lowercase   ,     verification_mode=lowercase   ,     base_path=lowercase   ,     num_proc=self.num_proc   ,     )
							SCREAMING_SNAKE_CASE     						= self.builder.as_dataset(
							    split=self.split   ,     verification_mode=lowercase   ,     in_memory=self.keep_in_memory			)
				return dataset





class     lowerCamelCase      :







	def __init__(     self      :Union[str, Any]   ,     lowercase      :Dataset   ,     lowercase      :Union[PathLike, BinaryIO]   ,     lowercase      :Optional[int] = None   ,     lowercase      :Optional[int] = None   ,     **lowercase      :List[str]   ,     )		->      Optional[Any]:







				"""simple docstring"""






				if num_proc is not None and num_proc <= 0:
							raise ValueError(f"""num_proc {num_proc} must be an integer > 0."""			)

				SCREAMING_SNAKE_CASE     						= dataset
				SCREAMING_SNAKE_CASE     						= path_or_buf
				SCREAMING_SNAKE_CASE     						= batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
				SCREAMING_SNAKE_CASE     						= num_proc
				SCREAMING_SNAKE_CASE     						= '''utf-8'''
				SCREAMING_SNAKE_CASE     						= to_json_kwargs







	def  snake_case__     (     self      :List[Any]			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.to_json_kwargs.pop('''path_or_buf'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= self.to_json_kwargs.pop('''orient'''   ,     '''records'''			)
				SCREAMING_SNAKE_CASE     						= self.to_json_kwargs.pop('''lines'''   ,     True if orient == '''records''' else False			)
				SCREAMING_SNAKE_CASE     						= self.to_json_kwargs.pop('''index'''   ,     False if orient in ['''split''', '''table'''] else True			)
				SCREAMING_SNAKE_CASE     						= self.to_json_kwargs.pop('''compression'''   ,     lowercase			)

				if compression not in [None, "infer", "gzip", "bz2", "xz"]:
							raise NotImplementedError(f"""`datasets` currently does not support {compression} compression"""			)

				if isinstance(self.path_or_buf   ,     (str, bytes, os.PathLike)			):
							with fsspec.open(self.path_or_buf   ,     '''wb'''   ,     compression=lowercase			) as buffer:
										SCREAMING_SNAKE_CASE     						= self._write(file_obj=lowercase   ,     orient=lowercase   ,     lines=lowercase   ,     index=lowercase   ,     **self.to_json_kwargs			)
				else:
							if compression:
										raise NotImplementedError(
										    f"""The compression parameter is not supported when writing to a buffer, but compression={compression}"""
										    ''' was passed. Please provide a local path instead.'''			)
							SCREAMING_SNAKE_CASE     						= self._write(
							    file_obj=self.path_or_buf   ,     orient=lowercase   ,     lines=lowercase   ,     index=lowercase   ,     **self.to_json_kwargs			)
				return written







	def  snake_case__     (     self      :Any   ,     lowercase      :List[Any]			)		->      Optional[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= args

				SCREAMING_SNAKE_CASE     						= query_table(
				    table=self.dataset.data   ,     key=slice(lowercase   ,     offset + self.batch_size			)   ,     indices=self.dataset._indices   ,     )
				SCREAMING_SNAKE_CASE     						= batch.to_pandas().to_json(
				    path_or_buf=lowercase   ,     orient=lowercase   ,     lines=lowercase   ,     index=lowercase   ,     **lowercase			)
				if not json_str.endswith('''\n'''			):
							json_str += "\n"
				return json_str.encode(self.encoding			)







	def  snake_case__     (     self      :Optional[int]   ,     lowercase      :BinaryIO   ,     lowercase      :Dict   ,     lowercase      :Any   ,     lowercase      :int   ,     **lowercase      :str   ,     )		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= 0

				if self.num_proc is None or self.num_proc == 1:
							for offset in logging.tqdm(
							    range(0   ,     len(self.dataset			)   ,     self.batch_size			)   ,     unit='''ba'''   ,     disable=not logging.is_progress_bar_enabled()   ,     desc='''Creating json from Arrow format'''   ,     ):
										SCREAMING_SNAKE_CASE     						= self._batch_json((offset, orient, lines, index, to_json_kwargs)			)
										written += file_obj.write(lowercase			)
				else:
							SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= len(self.dataset			), self.batch_size
							with multiprocessing.Pool(self.num_proc			) as pool:
										for json_str in logging.tqdm(
										    pool.imap(
										        self._batch_json   ,     [(offset, orient, lines, index, to_json_kwargs) for offset in range(0   ,     lowercase   ,     lowercase			)]   ,     )   ,     total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size   ,     unit='''ba'''   ,     disable=not logging.is_progress_bar_enabled()   ,     desc='''Creating json from Arrow format'''   ,     ):
													written += file_obj.write(lowercase			)

				return written

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


__lowerCAmelCase					   =       logging.get_logger(__name__)

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





class     lowerCamelCase      (       __lowerCamelCase					):
	UpperCamelCase_  :					Union[str, Any]    		=	'biogpt'







	def __init__(     self      :Tuple   ,     lowercase      :Union[str, Any]=4_2_3_8_4   ,     lowercase      :str=1_0_2_4   ,     lowercase      :Any=2_4   ,     lowercase      :List[str]=1_6   ,     lowercase      :List[str]=4_0_9_6   ,     lowercase      :int="gelu"   ,     lowercase      :List[Any]=0.1   ,     lowercase      :int=0.1   ,     lowercase      :int=1_0_2_4   ,     lowercase      :Optional[Any]=0.02   ,     lowercase      :Union[str, Any]=1e-12   ,     lowercase      :Tuple=True   ,     lowercase      :int=True   ,     lowercase      :Optional[int]=0.0   ,     lowercase      :Any=0.0   ,     lowercase      :str=1   ,     lowercase      :Any=0   ,     lowercase      :int=2   ,     **lowercase      :Tuple   ,     )		->      Optional[int]:







				"""simple docstring"""






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