





import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')

def     __A      (			a_						:Tuple)		->		Tuple:
				__a :						List[str]			       =  test_file.split(os.path.sep)
				if components[0:2] != ["tests", "models"]:
								raise ValueError(
								    '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
								    F"""{test_file} instead.""")
				__a :						List[Any]			       =  components[-1]
				if not test_fn.endswith('''py'''):
								raise ValueError(F"""`test_file` should be a python file. Got {test_fn} instead.""")
				if not test_fn.startswith('''test_modeling_'''):
								raise ValueError(
								    F"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.""")

				__a :						List[Any]			       =  components[:-1] + [test_fn.replace('''.py'''   ,       '''''')]
				__a :						Union[str, Any]			       =  '''.'''.join(UpperCamelCase__)

				return test_module_path

def     __A      (			a_						:Dict)		->		List[str]:
				__a :						Tuple			       =  get_module_path(UpperCamelCase__)
				__a :						Tuple			       =  importlib.import_module(UpperCamelCase__)

				return test_module

def     __A      (			a_						:int)		->		str:
				__a :						int			       =  []
				__a :						int			       =  get_test_module(UpperCamelCase__)
				for attr in dir(UpperCamelCase__):
								if attr.endswith('''ModelTester'''):
												tester_classes.append(getattr(UpperCamelCase__   ,       UpperCamelCase__))

    # sort with class names
				return sorted(UpperCamelCase__   ,       key=lambda a_: x.__name__)

def     __A      (			a_						:Optional[int])		->		Union[str, Any]:
				__a :						List[Any]			       =  []
				__a :						Any			       =  get_test_module(UpperCamelCase__)
				for attr in dir(UpperCamelCase__):
								__a :						Optional[Any]			       =  getattr(UpperCamelCase__   ,       UpperCamelCase__)
								# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
								# `all_model_classes` is not empty (which also excludes other special classes).
								__a :						Union[str, Any]			       =  getattr(UpperCamelCase__   ,       '''all_model_classes'''   ,       [])
								if len(UpperCamelCase__) > 0:
												test_classes.append(UpperCamelCase__)

    # sort with class names
				return sorted(UpperCamelCase__   ,       key=lambda a_: x.__name__)

def     __A      (			a_						:Optional[Any])		->		List[Any]:
				__a :						List[Any]			       =  get_test_classes(UpperCamelCase__)
				__a :						Dict			       =  set()
				for test_class in test_classes:
								model_classes.update(test_class.all_model_classes)

				# sort with class names
				return sorted(UpperCamelCase__   ,       key=lambda a_: x.__name__)

def     __A      (			a_						:str)		->		List[str]:
				__a :						str			       =  test_class()
				if hasattr(UpperCamelCase__   ,       '''setUp'''):
								test.setUp()

				__a :						int			       =  None
				if hasattr(UpperCamelCase__   ,       '''model_tester'''):
								# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
								if test.model_tester is not None:
												__a :						Optional[int]			       =  test.model_tester.__class__

				return model_tester

def     __A      (			a_						:Any   ,       a_						:List[str])		->		List[Any]:
				__a :						List[Any]			       =  get_test_classes(UpperCamelCase__)

				__a :						Any			       =  []
				for test_class in test_classes:
								if model_class in test_class.all_model_classes:
												target_test_classes.append(UpperCamelCase__)

    # sort with class names
				return sorted(UpperCamelCase__   ,       key=lambda a_: x.__name__)

def     __A      (			a_						:Tuple   ,       a_						:Tuple)		->		List[Any]:
				__a :						Optional[Any]			       =  get_test_classes_for_model(UpperCamelCase__   ,       UpperCamelCase__)

				__a :						str			       =  []
				for test_class in test_classes:
								__a :						str			       =  get_model_tester_from_test_class(UpperCamelCase__)
								if tester_class is not None:
												tester_classes.append(UpperCamelCase__)

    # sort with class names
				return sorted(UpperCamelCase__   ,       key=lambda a_: x.__name__)

def     __A      (			a_						:Optional[Any])		->		Optional[Any]:
				__a :						Tuple			       =  get_test_classes(UpperCamelCase__)
				__a :						List[str]			       =  {test_class: get_model_tester_from_test_class(UpperCamelCase__) for test_class in test_classes}
				return test_tester_mapping

def     __A      (			a_						:List[str])		->		List[Any]:
				__a :						Optional[int]			       =  get_model_classes(UpperCamelCase__)
				__a :						List[Any]			       =  {
				    model_class: get_test_classes_for_model(UpperCamelCase__   ,       UpperCamelCase__) for model_class in model_classes
				}
				return model_test_mapping

def     __A      (			a_						:Optional[int])		->		Union[str, Any]:
				__a :						int			       =  get_model_classes(UpperCamelCase__)
				__a :						Optional[Any]			       =  {
				    model_class: get_tester_classes_for_model(UpperCamelCase__   ,       UpperCamelCase__) for model_class in model_classes
				}
				return model_to_tester_mapping






def     __A      (			a_						:str)		->		Optional[int]:
				if isinstance(UpperCamelCase__   ,       UpperCamelCase__):
								return o
				elif isinstance(UpperCamelCase__   ,       UpperCamelCase__):
								return o.__name__
				elif isinstance(UpperCamelCase__   ,       (list, tuple)):
								return [to_json(UpperCamelCase__) for x in o]
				elif isinstance(UpperCamelCase__   ,       UpperCamelCase__):
								return {to_json(UpperCamelCase__): to_json(UpperCamelCase__) for k, v in o.items()}
				else:
								return o






"""simple docstring"""






import copy
import os
from typing import Union

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


A 			=  logging.get_logger(__name__)

A 			=  {
    '''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resolve/main/config.json''',
}




class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  '''git_vision_model'''







					def __init__(						self	,			_UpperCAmelCase=768	,			_UpperCAmelCase=3072	,			_UpperCAmelCase=12	,			_UpperCAmelCase=12	,			_UpperCAmelCase=3	,			_UpperCAmelCase=224	,			_UpperCAmelCase=16	,			_UpperCAmelCase="quick_gelu"	,			_UpperCAmelCase=1e-5	,			_UpperCAmelCase=0.0	,			_UpperCAmelCase=0.0_2	,			**_UpperCAmelCase	,			):
									super().__init__(**_UpperCAmelCase     )

									__a :						Union[str, Any]			       =  hidden_size
									__a :						Optional[int]			       =  intermediate_size
									__a :						Tuple			       =  num_hidden_layers
									__a :						Tuple			       =  num_attention_heads
									__a :						Optional[int]			       =  num_channels
									__a :						Tuple			       =  patch_size
									__a :						Any			       =  image_size
									__a :						Optional[Any]			       =  initializer_range
									__a :						Optional[int]			       =  attention_dropout
									__a :						Any			       =  layer_norm_eps
									__a :						Dict			       =  hidden_act







					@classmethod
					def  _lowerCamelCase		(						cls	,			_UpperCAmelCase	,			**_UpperCAmelCase     ):
									cls._set_token_in_kwargs(_UpperCAmelCase     )

									__a       ,						__a :						Dict			       =  cls.get_config_dict(_UpperCAmelCase	,			**_UpperCAmelCase     )

									# get the vision config dict if we are loading from GITConfig
									if config_dict.get('''model_type'''     ) == "git":
													__a :						int			       =  config_dict['''vision_config''']

									if "model_type" in config_dict and hasattr(cls	,			'''model_type'''     ) and config_dict["model_type"] != cls.model_type:
													logger.warning(
													    f"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
													    f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""     )

									return cls.from_dict(_UpperCAmelCase	,			**_UpperCAmelCase     )






class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  '''git'''







					def __init__(						self	,			_UpperCAmelCase=None	,			_UpperCAmelCase=30522	,			_UpperCAmelCase=768	,			_UpperCAmelCase=6	,			_UpperCAmelCase=12	,			_UpperCAmelCase=3072	,			_UpperCAmelCase="gelu"	,			_UpperCAmelCase=0.1	,			_UpperCAmelCase=0.1	,			_UpperCAmelCase=1024	,			_UpperCAmelCase=0.0_2	,			_UpperCAmelCase=1e-1_2	,			_UpperCAmelCase=0	,			_UpperCAmelCase="absolute"	,			_UpperCAmelCase=True	,			_UpperCAmelCase=False	,			_UpperCAmelCase=101	,			_UpperCAmelCase=102	,			_UpperCAmelCase=None	,			**_UpperCAmelCase	,			):
									super().__init__(bos_token_id=_UpperCAmelCase	,			eos_token_id=_UpperCAmelCase	,			pad_token_id=_UpperCAmelCase	,			**_UpperCAmelCase     )

									if vision_config is None:
													__a :						Union[str, Any]			       =  {}
													logger.info('''vision_config is None. initializing the GitVisionConfig with default values.'''     )

									__a :						Union[str, Any]			       =  GitVisionConfig(**_UpperCAmelCase     )
									__a :						List[str]			       =  vocab_size
									__a :						Any			       =  hidden_size
									__a :						Dict			       =  num_hidden_layers
									__a :						Tuple			       =  num_attention_heads
									__a :						List[str]			       =  hidden_act
									__a :						Any			       =  intermediate_size
									__a :						int			       =  hidden_dropout_prob
									__a :						Dict			       =  attention_probs_dropout_prob
									__a :						Tuple			       =  max_position_embeddings
									__a :						int			       =  initializer_range
									__a :						List[str]			       =  layer_norm_eps
									__a :						Tuple			       =  position_embedding_type
									__a :						Optional[int]			       =  use_cache
									__a :						str			       =  tie_word_embeddings
									__a :						Optional[Any]			       =  num_image_with_embedding

									__a :						str			       =  bos_token_id
									__a :						Dict			       =  eos_token_id







					def  _lowerCamelCase		(						self     ):
									__a :						Optional[int]			       =  copy.deepcopy(self.__dict__     )
									__a :						int			       =  self.vision_config.to_dict()
									__a :						Tuple			       =  self.__class__.model_type
									return output