


"""simple docstring"""





from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader




class 			lowercase__			(      A    ):
							'''simple docstring'''







							def __init__(  self	,       snake_case	,       snake_case = None	,       snake_case = None	,       snake_case = True	,       snake_case = None	,       snake_case = False	,       snake_case = None	,       snake_case = True	,       snake_case = "arrow"	,       **snake_case	,       )			->							Optional[int]:
									super().__init__(
									    split=snake_case	,       features=snake_case	,       cache_dir=snake_case	,       keep_in_memory=snake_case	,       streaming=snake_case	,       **snake_case	,       )
									_UpperCAmelCase							 =		load_from_cache_file
									_UpperCAmelCase							 =		file_format
									_UpperCAmelCase							 =		Spark(
									    df=snake_case	,       features=snake_case	,       cache_dir=snake_case	,       working_dir=snake_case	,       **snake_case	,       )






							def        lowerCamelCase_   (  self						)			->							Optional[Any]:
									if self.streaming:
											return self.builder.as_streaming_dataset(split=self.split						)
									_UpperCAmelCase							 =		None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
									self.builder.download_and_prepare(
									    download_mode=snake_case	,       file_format=self._file_format	,       )
									return self.builder.as_dataset(split=self.split						)







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase  							=					{
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase  							=					['''MvpTokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase  							=					[
					    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''MvpForCausalLM''',
					    '''MvpForConditionalGeneration''',
					    '''MvpForQuestionAnswering''',
					    '''MvpForSequenceClassification''',
					    '''MvpModel''',
					    '''MvpPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
					from .tokenization_mvp import MvpTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mvp_fast import MvpTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mvp import (
										    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MvpForCausalLM,
										    MvpForConditionalGeneration,
										    MvpForQuestionAnswering,
										    MvpForSequenceClassification,
										    MvpModel,
										    MvpPreTrainedModel,
										)

else:
					import sys

					lowercase  							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


