code: from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_torch_available,
      is_vision_available,
  )
  
  
  lowercase__    :       Union[str, Any]						=			{
      '''configuration_sam''': [
          '''SAM_PRETRAINED_CONFIG_ARCHIVE_MAP''',
          '''SamConfig''',
          '''SamMaskDecoderConfig''',
          '''SamPromptEncoderConfig''',
          '''SamVisionConfig''',
      ],
      '''processing_sam''': ['''SamProcessor'''],
  }
  
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	lowercase__    :       Any						=			[
  	    '''SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
  	    '''SamModel''',
  	    '''SamPreTrainedModel''',
  	]
  try:
  	if not is_tf_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	lowercase__    :       List[Any]						=			[
  	    '''TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST''',
  	    '''TFSamModel''',
  	    '''TFSamPreTrainedModel''',
  	]
  try:
  	if not is_vision_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	lowercase__    :       List[Any]						=			['''SamImageProcessor''']
  
  
  if TYPE_CHECKING:
  	from .configuration_sam import (
  	    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
  	    SamConfig,
  	    SamMaskDecoderConfig,
  	    SamPromptEncoderConfig,
  	    SamVisionConfig,
  	)
  	from .processing_sam import SamProcessor
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel
  
  	try:
  		if not is_tf_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel
  
  	try:
  		if not is_vision_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .image_processing_sam import SamImageProcessor
  
  else:
  	import sys
  
  	lowercase__    :       Dict						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
style_context: import glob
  import os
  
  from get_test_info import get_tester_classes
  
  
  if __name__ == "__main__":
  	lowercase__    :       List[Any]						=			[]
  
  	lowercase__    :       Optional[Any]						=			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
  	lowercase__    :       Optional[int]						=			glob.glob(pattern)
  	# TODO: deal with TF/Flax too
  	lowercase__    :       Dict						=			[
  	    x for x in test_files if not (x.startswith('''test_modeling_tf_''') or x.startswith('''test_modeling_flax_'''))
  	]
  
  	for test_file in test_files:
  		lowercase__    :       Tuple						=			get_tester_classes(test_file)
  		for tester_class in tester_classes:
  			# A few tester classes don't have `parent` parameter in `__init__`.
  			# TODO: deal this better
  			try:
  				lowercase__    :       Union[str, Any]						=			tester_class(parent=None)
  			except Exception:
  				continue
  			if hasattr(tester, '''get_config'''):
  				lowercase__    :       Union[str, Any]						=			tester.get_config()
  				for k, v in config.to_dict().items():
  					if isinstance(v, int):
  						lowercase__    :       int						=			None
  						if k in ["vocab_size"]:
  							lowercase__    :       Optional[int]						=			1_0_0
  						elif k in ["max_position_embeddings"]:
  							lowercase__    :       Union[str, Any]						=			1_2_8
  						elif k in ["hidden_size", "d_model"]:
  							lowercase__    :       Optional[Any]						=			4_0
  						elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
  							lowercase__    :       Dict						=			5
  						if target is not None and v > target:
  							failures.append(
  							    f'{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'
  							    f' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'
  							    f' than {target}.'
  							)
  
  	if len(failures) > 0:
  		raise Exception(f'There were {len(failures)} failures:\n' + '''\n'''.join(failures))
  
  
  
  