





"""simple docstring"""
import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


__UpperCamelCase     :						int						       =  pytest.mark.integration

@pytest.mark.parametrize('path'  ,     ['paws', 'csv']			)
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict  ,     _UpperCAmelCase					:    Optional[int]			):
 inspect_dataset(_UpperCAmelCase  ,     _UpperCAmelCase			)
 lowerCAmelCase    				= path + '.py'
 assert script_name in os.listdir(_UpperCAmelCase			)
 assert "__pycache__" not in os.listdir(_UpperCAmelCase			)

@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'			)
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'			)
@pytest.mark.parametrize('path'  ,     ['accuracy']			)
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    int			):
 inspect_metric(_UpperCAmelCase  ,     _UpperCAmelCase			)
 lowerCAmelCase    				= path + '.py'
 assert script_name in os.listdir(_UpperCAmelCase			)
 assert "__pycache__" not in os.listdir(_UpperCAmelCase			)

@pytest.mark.parametrize(
    'path, config_name, expected_splits'  ,     [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str  ,     _UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= get_dataset_config_info(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)
 assert info.config_name == config_name
 assert list(info.splits.keys()			) == expected_splits

@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,     [
        ('paws', None, ValueError),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Optional[int]  ,     _UpperCAmelCase					:    List[str]  ,     _UpperCAmelCase					:    List[Any]			):
 with pytest.raises(_UpperCAmelCase			):
  get_dataset_config_info(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)

@pytest.mark.parametrize(
    'path, expected'  ,     [
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[str]  ,     _UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= get_dataset_config_names(_UpperCAmelCase			)
 assert expected in config_names

@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'  ,     [
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[Any]  ,     _UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    List[str]			):
 lowerCAmelCase    				= get_dataset_infos(_UpperCAmelCase			)
 assert list(infos.keys()			) == expected_configs
 lowerCAmelCase    				= expected_configs[0]
 assert expected_config in infos
 lowerCAmelCase    				= infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys()			) == expected_splits_in_first_config

@pytest.mark.parametrize(
    'path, expected_config, expected_splits'  ,     [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any  ,     _UpperCAmelCase					:    Optional[Any]  ,     _UpperCAmelCase					:    str			):
 lowerCAmelCase    				= get_dataset_infos(_UpperCAmelCase			)
 assert expected_config in infos
 lowerCAmelCase    				= infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys()			) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,     [
        ('paws', None, ValueError),
    ]  ,     )
def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Tuple  ,     _UpperCAmelCase					:    Tuple  ,     _UpperCAmelCase					:    Union[str, Any]			):
 with pytest.raises(_UpperCAmelCase			):
  get_dataset_split_names(_UpperCAmelCase  ,     config_name=_UpperCAmelCase			)











from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
   from ..ta.tokenization_ta import TaTokenizer
else:
   from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCamelCase__					:  List[Any]      							=				TaTokenizer

if is_tokenizers_available():
   from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
   from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCamelCase__					:  Union[str, Any]      							=				TaTokenizerFast

lowerCamelCase__					:  Dict      							=				{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				[
       'MT5EncoderModel',
       'MT5ForConditionalGeneration',
       'MT5ForQuestionAnswering',
       'MT5Model',
       'MT5PreTrainedModel',
       'MT5Stack',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
   from .configuration_mta import MTaConfig, MTaOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mta import (
          MTaEncoderModel,
          MTaForConditionalGeneration,
          MTaForQuestionAnswering,
          MTaModel,
          MTaPreTrainedModel,
          MTaStack,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
   import sys

   lowerCamelCase__					:  int      							=				_LazyModule(
       __name__,
       globals()['__file__'],
       _import_structure,
       extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
       module_spec=__spec__,
   )