


'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase    :     Union[str, Any]					=						{
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Tuple					=						['''DistilBertTokenizerFast''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Tuple					=						[
           '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''DistilBertForMaskedLM''',
           '''DistilBertForMultipleChoice''',
           '''DistilBertForQuestionAnswering''',
           '''DistilBertForSequenceClassification''',
           '''DistilBertForTokenClassification''',
           '''DistilBertModel''',
           '''DistilBertPreTrainedModel''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     List[str]					=						[
           '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''TFDistilBertForMaskedLM''',
           '''TFDistilBertForMultipleChoice''',
           '''TFDistilBertForQuestionAnswering''',
           '''TFDistilBertForSequenceClassification''',
           '''TFDistilBertForTokenClassification''',
           '''TFDistilBertMainLayer''',
           '''TFDistilBertModel''',
           '''TFDistilBertPreTrainedModel''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Optional[int]					=						[
           '''FlaxDistilBertForMaskedLM''',
           '''FlaxDistilBertForMultipleChoice''',
           '''FlaxDistilBertForQuestionAnswering''',
           '''FlaxDistilBertForSequenceClassification''',
           '''FlaxDistilBertForTokenClassification''',
           '''FlaxDistilBertModel''',
           '''FlaxDistilBertPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_distilbert import (
           DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DistilBertConfig,
           DistilBertOnnxConfig,
       )
       from .tokenization_distilbert import DistilBertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_distilbert_fast import DistilBertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_distilbert import (
                  DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DistilBertForMaskedLM,
                  DistilBertForMultipleChoice,
                  DistilBertForQuestionAnswering,
                  DistilBertForSequenceClassification,
                  DistilBertForTokenClassification,
                  DistilBertModel,
                  DistilBertPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_distilbert import (
                  TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFDistilBertForMaskedLM,
                  TFDistilBertForMultipleChoice,
                  TFDistilBertForQuestionAnswering,
                  TFDistilBertForSequenceClassification,
                  TFDistilBertForTokenClassification,
                  TFDistilBertMainLayer,
                  TFDistilBertModel,
                  TFDistilBertPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_distilbert import (
                  FlaxDistilBertForMaskedLM,
                  FlaxDistilBertForMultipleChoice,
                  FlaxDistilBertForQuestionAnswering,
                  FlaxDistilBertForSequenceClassification,
                  FlaxDistilBertForTokenClassification,
                  FlaxDistilBertModel,
                  FlaxDistilBertPreTrainedModel,
              )

else:
       import sys

       lowerCAmelCase    :     List[str]					=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





'''simple docstring'''







import unittest

from knapsack import greedy_knapsack as kp
class 	UpperCamelCase__					( unittest.TestCase	):



     """simple docstring"""






     def a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       [10, 20, 30, 40, 50, 60]
            _lowerCAmelCase    :							Union[str, Any]   			=       [2, 4, 6, 8, 10, 12]
            _lowerCAmelCase    :							Dict   			=       100
            self.assertEqual(kp.calc_profit(snake_case__      ,	snake_case__      ,	snake_case__   )      ,	210   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'max_weight must greater than zero.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'Weight can not be negative.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'Profit can not be negative.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(snake_case__      ,	'max_weight must greater than zero.'   )







     def a	( self   ):

            '''simple docstring'''

            self.assertRaisesRegex(
                snake_case__      ,	'The length of profit and weight must be same.'   )


if __name__ == "__main__":
       unittest.main()

