

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     __snake_case    (				snake_case__  ):
       """simple docstring"""







       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase = None      , _UpperCamelCase = None      , _UpperCamelCase = None      , _UpperCamelCase = False      , _UpperCamelCase = False      , _UpperCamelCase = None      , _UpperCamelCase = None      , **_UpperCamelCase      , )      ->							Any:






              """simple docstring"""


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






       def 			a		(		self   )      ->							str:






              """simple docstring"""


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

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






class     __snake_case    :
       """simple docstring"""







       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase      , _UpperCamelCase = None      , _UpperCamelCase = None      , **_UpperCamelCase      , )      ->							List[str]:






              """simple docstring"""


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

              __snake_case       	=							dataset
              __snake_case       	=							path_or_buf
              __snake_case       	=							batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
              __snake_case       	=							num_proc
              __snake_case       	=							"""utf-8"""
              __snake_case       	=							to_json_kwargs


       def 			a		(		self   )      ->							int:






              """simple docstring"""


              __snake_case       	=							self.to_json_kwargs.pop("""path_or_buf"""      , _UpperCamelCase   )
              __snake_case       	=							self.to_json_kwargs.pop("""orient"""      , """records"""   )
              __snake_case       	=							self.to_json_kwargs.pop("""lines"""      , True if orient == """records""" else False   )
              __snake_case       	=							self.to_json_kwargs.pop("""index"""      , False if orient in ["""split""", """table"""] else True   )
              __snake_case       	=							self.to_json_kwargs.pop("""compression"""      , _UpperCamelCase   )

              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=_UpperCamelCase   ) as buffer:
                            __snake_case       	=							self._write(file_obj=_UpperCamelCase      , orient=_UpperCamelCase      , lines=_UpperCamelCase      , index=_UpperCamelCase      , **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."""   )
                     __snake_case       	=							self._write(
                         file_obj=self.path_or_buf      , orient=_UpperCamelCase      , lines=_UpperCamelCase      , index=_UpperCamelCase      , **self.to_json_kwargs   )
              return written


       def 			a		(		self      , _UpperCamelCase   )      ->							Optional[int]:






              """simple docstring"""


              __snake_case	,    __snake_case	,    __snake_case	,    __snake_case	,    __snake_case       	=							args

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






       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase      , _UpperCamelCase      , _UpperCamelCase      , **_UpperCamelCase      , )      ->							int:






              """simple docstring"""


              __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"""      , ):
                            __snake_case       	=							self._batch_json((offset, orient, lines, index, to_json_kwargs)   )
                            written += file_obj.write(_UpperCamelCase   )
              else:
                     __snake_case	,    __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      , _UpperCamelCase      , _UpperCamelCase   )]      , )      , 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(_UpperCamelCase   )

              return written




import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


UpperCamelCase__		 =     logging.get_logger(__name__)

class     __snake_case    (				snake_case__  ):
       """simple docstring"""







       def __init__(		self      , *_UpperCamelCase      , **_UpperCamelCase   )      ->							None:






              """simple docstring"""


              warnings.warn(
                  """The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
                  """ use YolosImageProcessor instead."""      , _UpperCamelCase      , )
              super().__init__(*_UpperCamelCase      , **_UpperCamelCase   )

