





'''simple docstring'''


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


_lowerCamelCase					:						Dict					     =							logging.get_logger(__name__)

_lowerCamelCase					:						List[Any]					     =							{
    'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/config.json',
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}



class 				__UpperCAmelCase	(							__A    ):







		'''simple docstring'''







		__lowerCAmelCase								=     "qdqbert"







		def __init__(self    :   Dict   ,   _lowerCAmelCase    :   List[Any]=3_0522   ,   _lowerCAmelCase    :   Optional[int]=768   ,   _lowerCAmelCase    :   Dict=12   ,   _lowerCAmelCase    :   Union[str, Any]=12   ,   _lowerCAmelCase    :   Tuple=3072   ,   _lowerCAmelCase    :   List[Any]="gelu"   ,   _lowerCAmelCase    :   Tuple=0.1   ,   _lowerCAmelCase    :   str=0.1   ,   _lowerCAmelCase    :   Dict=512   ,   _lowerCAmelCase    :   str=2   ,   _lowerCAmelCase    :   int=0.02   ,   _lowerCAmelCase    :   int=1e-12   ,   _lowerCAmelCase    :   Union[str, Any]=True   ,   _lowerCAmelCase    :   Optional[int]=1   ,   _lowerCAmelCase    :   Optional[int]=0   ,   _lowerCAmelCase    :   Any=2   ,   **_lowerCAmelCase    :   Any   ,   ):
			super().__init__(pad_token_id=lowercase_   ,   bos_token_id=lowercase_   ,   eos_token_id=lowercase_   ,   **lowercase_   )

			A					=   vocab_size
			A					=   max_position_embeddings
			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					=   type_vocab_size
			A					=   layer_norm_eps
			A					=   use_cache


import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
      from PIL import Image



class     snake_case_			(						unittest.TestCase    ,__A			):






   def  __UpperCamelCase	( self							:	int    )   ->		Union[str, Any]:
       lowercase__					:  Any          =							load_tool("image-segmentation"    )
       self.tool.setup()
       lowercase__					:  Optional[int]          =							load_tool("image-segmentation"      ,		remote=lowercase_    )






   def  __UpperCamelCase	( self							:	Any    )   ->		Tuple:
       lowercase__					:  Any          =							Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"    )    ) / "000000039769.png"    )
       lowercase__					:  Tuple          =							self.tool(lowercase_      ,		"cat"    )
       self.assertTrue(isinstance(lowercase_      ,		Image.Image    )    )






   def  __UpperCamelCase	( self							:	Optional[int]    )   ->		Dict:
       lowercase__					:  List[Any]          =							Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"    )    ) / "000000039769.png"    )
       lowercase__					:  Optional[int]          =							self.remote_tool(lowercase_      ,		"cat"    )
       self.assertTrue(isinstance(lowercase_      ,		Image.Image    )    )






   def  __UpperCamelCase	( self							:	List[Any]    )   ->		Dict:
       lowercase__					:  Optional[Any]          =							Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"    )    ) / "000000039769.png"    )
       lowercase__					:  int          =							self.tool(image=lowercase_      ,		label="cat"    )
       self.assertTrue(isinstance(lowercase_      ,		Image.Image    )    )







   def  __UpperCamelCase	( self							:	Dict    )   ->		List[Any]:
       lowercase__					:  Tuple          =							Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"    )    ) / "000000039769.png"    )
       lowercase__					:  Union[str, Any]          =							self.remote_tool(image=lowercase_      ,		label="cat"    )
       self.assertTrue(isinstance(lowercase_      ,		Image.Image    )    )



