'''simple docstring'''




import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin






class 		__A       (unittest.TestCase ,					__magic_name__   ):






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				str       				=		load_tool("text-classification"      )
              self.tool.setup()
              __UpperCAmelCase  :				Any       				=		load_tool("text-classification"				,     remote=UpperCamelCase_      )






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		self.tool("That's quite cool"				,     ["positive", "negative"]      )
              self.assertEqual(UpperCamelCase_				,     "positive"      )






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				str       				=		self.remote_tool("That's quite cool"				,     ["positive", "negative"]      )
              self.assertEqual(UpperCamelCase_				,     "positive"      )






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				List[str]       				=		self.tool(text="That's quite cool"				,     labels=["positive", "negative"]      )
              self.assertEqual(UpperCamelCase_				,     "positive"      )







       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		self.remote_tool(text="That's quite cool"				,     labels=["positive", "negative"]      )
              self.assertEqual(UpperCamelCase_				,     "positive"      )







'''simple docstring'''




from typing import TYPE_CHECKING

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


_a   :	Dict 							=   {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"]}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	Dict 							=   ["ReformerTokenizer"]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	List[Any] 							=   ["ReformerTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	int 							=   [
       "REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
       "ReformerAttention",
       "ReformerForMaskedLM",
       "ReformerForQuestionAnswering",
       "ReformerForSequenceClassification",
       "ReformerLayer",
       "ReformerModel",
       "ReformerModelWithLMHead",
       "ReformerPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_reformer import ReformerTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_reformer_fast import ReformerTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_reformer import (
          REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          ReformerAttention,
          ReformerForMaskedLM,
          ReformerForQuestionAnswering,
          ReformerForSequenceClassification,
          ReformerLayer,
          ReformerModel,
          ReformerModelWithLMHead,
          ReformerPreTrainedModel,
      )

else:
   import sys

   _a   :	Optional[int] 							=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






