





from typing import TYPE_CHECKING

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


_UpperCamelCase   :							List[Any]     =	{"""configuration_gptj""": ["""GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTJConfig""", """GPTJOnnxConfig"""]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase   :							List[Any]     =	[
        """GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """GPTJForCausalLM""",
        """GPTJForQuestionAnswering""",
        """GPTJForSequenceClassification""",
        """GPTJModel""",
        """GPTJPreTrainedModel""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase   :							Union[str, Any]     =	[
        """TFGPTJForCausalLM""",
        """TFGPTJForQuestionAnswering""",
        """TFGPTJForSequenceClassification""",
        """TFGPTJModel""",
        """TFGPTJPreTrainedModel""",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase   :							Union[str, Any]     =	[
        """FlaxGPTJForCausalLM""",
        """FlaxGPTJModel""",
        """FlaxGPTJPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig, GPTJOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gptj import (
            GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPTJForCausalLM,
            GPTJForQuestionAnswering,
            GPTJForSequenceClassification,
            GPTJModel,
            GPTJPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_gptj import (
            TFGPTJForCausalLM,
            TFGPTJForQuestionAnswering,
            TFGPTJForSequenceClassification,
            TFGPTJModel,
            TFGPTJPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel

else:
    import sys

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








import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


_UpperCamelCase   :							str     =	"""
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
"""







class 						_lowerCAmelCase(						unittest.TestCase		,   _a):

  """simple docstring"""







  def 		SCREAMING_SNAKE_CASE__	( self     )-> int:
     __A				 =       load_tool('''summarization'''     )
     self.tool.setup()
     __A				 =       load_tool('''summarization'''  ,    remote=UpperCAmelCase     )

  def 		SCREAMING_SNAKE_CASE__	( self     )-> List[str]:
     __A				 =       self.tool(UpperCAmelCase     )
     self.assertEqual(
         UpperCAmelCase  ,    '''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''  ,    )

  def 		SCREAMING_SNAKE_CASE__	( self     )-> Dict:
     __A				 =       self.remote_tool(UpperCAmelCase     )
     self.assertEqual(
         UpperCAmelCase  ,    '''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''  ,    )

  def 		SCREAMING_SNAKE_CASE__	( self     )-> Union[str, Any]:
     __A				 =       self.tool(text=UpperCAmelCase     )
     self.assertEqual(
         UpperCAmelCase  ,    '''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''  ,    )





  def 		SCREAMING_SNAKE_CASE__	( self     )-> Optional[Any]:
     __A				 =       self.remote_tool(text=UpperCAmelCase     )
     self.assertEqual(
         UpperCAmelCase  ,    '''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''  ,    )

