






from typing import TYPE_CHECKING

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


snake_case__      :	Tuple       	=      {
    """configuration_mobilebert""": [
        """MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileBertConfig""",
        """MobileBertOnnxConfig""",
    ],
    """tokenization_mobilebert""": ["""MobileBertTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__      :	Tuple       	=      ["""MobileBertTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__      :	Optional[int]       	=      [
     """MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """MobileBertForMaskedLM""",
     """MobileBertForMultipleChoice""",
     """MobileBertForNextSentencePrediction""",
     """MobileBertForPreTraining""",
     """MobileBertForQuestionAnswering""",
     """MobileBertForSequenceClassification""",
     """MobileBertForTokenClassification""",
     """MobileBertLayer""",
     """MobileBertModel""",
     """MobileBertPreTrainedModel""",
     """load_tf_weights_in_mobilebert""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__      :	int       	=      [
     """TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFMobileBertForMaskedLM""",
     """TFMobileBertForMultipleChoice""",
     """TFMobileBertForNextSentencePrediction""",
     """TFMobileBertForPreTraining""",
     """TFMobileBertForQuestionAnswering""",
     """TFMobileBertForSequenceClassification""",
     """TFMobileBertForTokenClassification""",
     """TFMobileBertMainLayer""",
     """TFMobileBertModel""",
     """TFMobileBertPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_mobilebert import (
     MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     MobileBertConfig,
     MobileBertOnnxConfig,
 )
 from .tokenization_mobilebert import MobileBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_mobilebert_fast import MobileBertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilebert import (
      MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileBertForMaskedLM,
      MobileBertForMultipleChoice,
      MobileBertForNextSentencePrediction,
      MobileBertForPreTraining,
      MobileBertForQuestionAnswering,
      MobileBertForSequenceClassification,
      MobileBertForTokenClassification,
      MobileBertLayer,
      MobileBertModel,
      MobileBertPreTrainedModel,
      load_tf_weights_in_mobilebert,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_mobilebert import (
      TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFMobileBertForMaskedLM,
      TFMobileBertForMultipleChoice,
      TFMobileBertForNextSentencePrediction,
      TFMobileBertForPreTraining,
      TFMobileBertForQuestionAnswering,
      TFMobileBertForSequenceClassification,
      TFMobileBertForTokenClassification,
      TFMobileBertMainLayer,
      TFMobileBertModel,
      TFMobileBertPreTrainedModel,
  )

else:
 import sys

 snake_case__      :	Any       	=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













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,
)


snake_case__      :	Optional[int]       	=      pytest.mark.integration






@pytest.mark.parametrize('path'    ,      ['paws', 'csv'])
def     _snake_case    (__lowercase    ,      __lowercase):
   inspect_dataset(__lowercase    ,      __lowercase)
   UpperCamelCase_									=     path + '.py'
   assert script_name in os.listdir(__lowercase)
   assert "__pycache__" not in os.listdir(__lowercase)






@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     _snake_case    (__lowercase    ,      __lowercase):
   inspect_metric(__lowercase    ,      __lowercase)
   UpperCamelCase_									=     path + '.py'
   assert script_name in os.listdir(__lowercase)
   assert "__pycache__" not in os.listdir(__lowercase)






@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     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   UpperCamelCase_									=     get_dataset_config_info(__lowercase    ,      config_name=__lowercase)
   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     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   with pytest.raises(__lowercase):
      get_dataset_config_info(__lowercase    ,      config_name=__lowercase)






@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     _snake_case    (__lowercase    ,      __lowercase):
   UpperCamelCase_									=     get_dataset_config_names(__lowercase)
   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     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   UpperCamelCase_									=     get_dataset_infos(__lowercase)
   assert list(infos.keys()) == expected_configs
   UpperCamelCase_									=     expected_configs[0]
   assert expected_config in infos
   UpperCamelCase_									=     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     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   UpperCamelCase_									=     get_dataset_infos(__lowercase)
   assert expected_config in infos
   UpperCamelCase_									=     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     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   with pytest.raises(__lowercase):
      get_dataset_split_names(__lowercase    ,      config_name=__lowercase)





