





'''simple docstring'''

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       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	Optional[Any]							,			A__      :	NestedDataStructureLike[PathLike]							,			A__      :	Optional[NamedSplit] = None							,			A__      :	Optional[Features] = None							,			A__      :	str = None							,			A__      :	bool = False							,			A__      :	bool = False							,			A__      :	Optional[str] = None							,			A__      :	Optional[int] = None							,			**A__      :	List[str]							,			)					-> Union[str, Any]:
						super().__init__(
						    A__							,			split=A__							,			features=A__							,			cache_dir=A__							,			keep_in_memory=A__							,			streaming=A__							,			num_proc=A__							,			**A__							,			)
						lowercase         = field
						lowercase         = path_or_paths if isinstance(A__							,			A__				) else {self.split: path_or_paths}
						lowercase         = Json(
						    cache_dir=A__							,			data_files=A__							,			features=A__							,			field=A__							,			**A__							,			)





		def 				UpperCAmelCase__   (self      :	Dict				)					-> str:
						# Build iterable dataset
						if self.streaming:
										lowercase         = self.builder.as_streaming_dataset(split=self.split				)
						# Build regular (map-style) dataset
						else:
										lowercase         = None
										lowercase         = None
										lowercase         = None
										lowercase         = None

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




class       UpperCAmelCase :




		def __init__(self      :	Union[str, Any]							,			A__      :	Dataset							,			A__      :	Union[PathLike, BinaryIO]							,			A__      :	Optional[int] = None							,			A__      :	Optional[int] = None							,			**A__      :	Optional[int]							,			)					-> str:
						if num_proc is not None and num_proc <= 0:
										raise ValueError(f'num_proc {num_proc} must be an integer > 0.'				)

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




		def 				UpperCAmelCase__   (self      :	Any				)					-> int:
						lowercase         = self.to_json_kwargs.pop("path_or_buf"							,			A__				)
						lowercase         = self.to_json_kwargs.pop("orient"							,			"records"				)
						lowercase         = self.to_json_kwargs.pop("lines"							,			True if orient == "records" else False				)
						lowercase         = self.to_json_kwargs.pop("index"							,			False if orient in ["split", "table"] else True				)
						lowercase         = self.to_json_kwargs.pop("compression"							,			A__				)

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




		def 				UpperCAmelCase__   (self      :	List[str]							,			A__      :	Dict				)					-> Optional[Any]:
						lowercase   ,							lowercase   ,							lowercase   ,							lowercase   ,							lowercase         = args

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





		def 				UpperCAmelCase__   (self      :	str							,			A__      :	BinaryIO							,			A__      :	Optional[int]							,			A__      :	List[str]							,			A__      :	Dict							,			**A__      :	Any							,			)					-> int:
						lowercase         = 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"							,			):
														lowercase         = self._batch_json((offset, orient, lines, index, to_json_kwargs)				)
														written += file_obj.write(A__				)
						else:
										lowercase   ,							lowercase         = 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							,			A__							,			A__				)]							,			)							,			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(A__				)

						return written











'''simple docstring'''

import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate

@dataclass(frozen=_lowercase  )
class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	str 			=		field(default='''image-classification'''			,       metadata={'''include_in_asdict_even_if_is_default''': True}  )
		UpperCAmelCase					:	ClassVar[Features] 			=		Features({'''image''': Image()}  )
		UpperCAmelCase					:	ClassVar[Features] 			=		Features({'''labels''': ClassLabel}  )
		UpperCAmelCase					:	str 			=		"image"
		UpperCAmelCase					:	str 			=		"labels"




		def 				UpperCAmelCase__   (self      :	List[str]							,			A__      :	Union[str, Any]				)					-> Union[str, Any]:
						if self.label_column not in features:
										raise ValueError(f'Column {self.label_column} is not present in features.'				)
						if not isinstance(features[self.label_column]							,			A__				):
										raise ValueError(f'Column {self.label_column} is not a ClassLabel.'				)
						lowercase         = copy.deepcopy(self				)
						lowercase         = self.label_schema.copy()
						lowercase         = features[self.label_column]
						lowercase         = label_schema
						return task_template





		@property
		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> Dict[str, str]:
						return {
						    self.image_column: "image",
						    self.label_column: "labels",
						}




