





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCamelCase   :							Dict     =	logging.get_logger(__name__)

_UpperCamelCase   :							Optional[int]     =	{
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}







class 						_lowerCAmelCase(						_a):

  """simple docstring"""







  lowerCamelCase__      					=   '''videomae'''

  def __init__( self  ,    UpperCAmelCase=2_24  ,    UpperCAmelCase=16  ,    UpperCAmelCase=3  ,    UpperCAmelCase=16  ,    UpperCAmelCase=2  ,    UpperCAmelCase=7_68  ,    UpperCAmelCase=12  ,    UpperCAmelCase=12  ,    UpperCAmelCase=30_72  ,    UpperCAmelCase="gelu"  ,    UpperCAmelCase=0.0  ,    UpperCAmelCase=0.0  ,    UpperCAmelCase=0.02  ,    UpperCAmelCase=1e-12  ,    UpperCAmelCase=True  ,    UpperCAmelCase=True  ,    UpperCAmelCase=6  ,    UpperCAmelCase=3_84  ,    UpperCAmelCase=4  ,    UpperCAmelCase=15_36  ,    UpperCAmelCase=True  ,    **UpperCAmelCase  ,    )-> Any:
     super().__init__(**UpperCAmelCase     )

     __A				 =       image_size
     __A				 =       patch_size
     __A				 =       num_channels
     __A				 =       num_frames
     __A				 =       tubelet_size

     __A				 =       hidden_size
     __A				 =       num_hidden_layers
     __A				 =       num_attention_heads
     __A				 =       intermediate_size
     __A				 =       hidden_act
     __A				 =       hidden_dropout_prob
     __A				 =       attention_probs_dropout_prob
     __A				 =       initializer_range
     __A				 =       layer_norm_eps
     __A				 =       qkv_bias
     __A				 =       use_mean_pooling

     __A				 =       decoder_num_attention_heads
     __A				 =       decoder_hidden_size
     __A				 =       decoder_num_hidden_layers
     __A				 =       decoder_intermediate_size
     __A				 =       norm_pix_loss








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.'''  ,    )

