


import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs





class  _a							(    _lowercase):




	def __init__( self						:		int		, _SCREAMING_SNAKE_CASE						:		Optional[Any]		, _SCREAMING_SNAKE_CASE						:		Optional[int]=None		, _SCREAMING_SNAKE_CASE						:		int=True		, _SCREAMING_SNAKE_CASE						:		Optional[int]=None		, **_SCREAMING_SNAKE_CASE						:		Tuple		)->	List[Any]:
			lowerCAmelCase__       :      int   					= parent
			lowerCAmelCase__       :      Optional[int]   					= config_class
			lowerCAmelCase__       :      Tuple   					= has_text_modality
			lowerCAmelCase__       :      Tuple   					= kwargs
			lowerCAmelCase__       :      Dict   					= common_properties




	def 							UpperCAmelCase__( self						:		Any		)->	int:
			lowerCAmelCase__       :      Union[str, Any]   					= self.config_class(**self.inputs_dict		)
			lowerCAmelCase__       :      Any   					= (
			    ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
			    if self.common_properties is None
			    else self.common_properties
			)

			# Add common fields for text models
			if self.has_text_modality:
					common_properties.extend(['''vocab_size''']		)

			# Test that config has the common properties as getters
			for prop in common_properties:
					self.parent.assertTrue(hasattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)		, msg=F'`{prop}` does not exist'		)

			# Test that config has the common properties as setter
			for idx, name in enumerate(_SCREAMING_SNAKE_CASE		):
					try:
							setattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)
							self.parent.assertEqual(
							    getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)		, _SCREAMING_SNAKE_CASE		, msg=F'`{name} value {idx} expected, but was {getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)}'		)
					except NotImplementedError:
							# Some models might not be able to implement setters for common_properties
							# In that case, a NotImplementedError is raised
							pass

        # Test if config class can be called with Config(prop_name=..)
			for idx, name in enumerate(_SCREAMING_SNAKE_CASE		):
					try:
							lowerCAmelCase__       :      str   					= self.config_class(**{name: idx}		)
							self.parent.assertEqual(
							    getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)		, _SCREAMING_SNAKE_CASE		, msg=F'`{name} value {idx} expected, but was {getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)}'		)
					except NotImplementedError:
							# Some models might not be able to implement setters for common_properties
							# In that case, a NotImplementedError is raised
							pass




	def 							UpperCAmelCase__( self						:		List[Any]		)->	Dict:
			lowerCAmelCase__       :      List[str]   					= self.config_class(**self.inputs_dict		)
			lowerCAmelCase__       :      Optional[int]   					= json.loads(config.to_json_string()		)
			for key, value in self.inputs_dict.items():
					self.parent.assertEqual(obj[key]		, _SCREAMING_SNAKE_CASE		)




	def 							UpperCAmelCase__( self						:		List[str]		)->	Union[str, Any]:
			lowerCAmelCase__       :      int   					= self.config_class(**self.inputs_dict		)

			with tempfile.TemporaryDirectory() as tmpdirname:
					lowerCAmelCase__       :      Optional[Any]   					= os.path.join(_SCREAMING_SNAKE_CASE		, '''config.json'''		)
					config_first.to_json_file(_SCREAMING_SNAKE_CASE		)
					lowerCAmelCase__       :      Optional[int]   					= self.config_class.from_json_file(_SCREAMING_SNAKE_CASE		)

			self.parent.assertEqual(config_second.to_dict()		, config_first.to_dict()		)




	def 							UpperCAmelCase__( self						:		List[Any]		)->	List[str]:
			lowerCAmelCase__       :      List[Any]   					= self.config_class(**self.inputs_dict		)

			with tempfile.TemporaryDirectory() as tmpdirname:
					config_first.save_pretrained(_SCREAMING_SNAKE_CASE		)
					lowerCAmelCase__       :      int   					= self.config_class.from_pretrained(_SCREAMING_SNAKE_CASE		)

			self.parent.assertEqual(config_second.to_dict()		, config_first.to_dict()		)




	def 							UpperCAmelCase__( self						:		Any		)->	int:
			lowerCAmelCase__       :      Tuple   					= self.config_class(**self.inputs_dict		)

			lowerCAmelCase__       :      str   					= '''test'''
			with tempfile.TemporaryDirectory() as tmpdirname:
					lowerCAmelCase__       :      Union[str, Any]   					= os.path.join(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		)
					config_first.save_pretrained(_SCREAMING_SNAKE_CASE		)
					lowerCAmelCase__       :      str   					= self.config_class.from_pretrained(_SCREAMING_SNAKE_CASE		, subfolder=_SCREAMING_SNAKE_CASE		)

			self.parent.assertEqual(config_second.to_dict()		, config_first.to_dict()		)




	def 							UpperCAmelCase__( self						:		Union[str, Any]		)->	Union[str, Any]:
			lowerCAmelCase__       :      List[str]   					= self.config_class(**self.inputs_dict		, num_labels=5		)
			self.parent.assertEqual(len(config.idalabel		)		, 5		)
			self.parent.assertEqual(len(config.labelaid		)		, 5		)

			lowerCAmelCase__       :      Any   					= 3
			self.parent.assertEqual(len(config.idalabel		)		, 3		)
			self.parent.assertEqual(len(config.labelaid		)		, 3		)




	def 							UpperCAmelCase__( self						:		Optional[Any]		)->	str:
			if self.config_class.is_composition:
					return
			lowerCAmelCase__       :      Dict   					= self.config_class()
			self.parent.assertIsNotNone(_SCREAMING_SNAKE_CASE		)




	def 							UpperCAmelCase__( self						:		Any		)->	Dict:
			lowerCAmelCase__       :      Dict   					= copy.deepcopy(_SCREAMING_SNAKE_CASE		)
			lowerCAmelCase__       :      List[Any]   					= self.config_class(**_SCREAMING_SNAKE_CASE		)
			lowerCAmelCase__       :      List[Any]   					= []
			for key, value in config_common_kwargs.items():
					if key == "torch_dtype":
							if not is_torch_available():
									continue
							else:
									import torch

									if config.torch_dtype != torch.floataa:
											wrong_values.append(('''torch_dtype''', config.torch_dtype, torch.floataa)		)
					elif getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		) != value:
							wrong_values.append((key, getattr(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		), value)		)

			if len(_SCREAMING_SNAKE_CASE		) > 0:
					lowerCAmelCase__       :      Union[str, Any]   					= '''\n'''.join([F'- {v[0]}: got {v[1]} instead of {v[2]}' for v in wrong_values]		)
					raise ValueError(F'The following keys were not properly set in the config:\n{errors}'		)




	def 							UpperCAmelCase__( self						:		Union[str, Any]		)->	Tuple:
			self.create_and_test_config_common_properties()
			self.create_and_test_config_to_json_string()
			self.create_and_test_config_to_json_file()
			self.create_and_test_config_from_and_save_pretrained()
			self.create_and_test_config_from_and_save_pretrained_subfolder()
			self.create_and_test_config_with_num_labels()
			self.check_config_can_be_init_without_params()
			self.check_config_arguments_init()








from typing import TYPE_CHECKING

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


lowerCamelCase						=		{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		['''BeitFeatureExtractor''']
		lowerCamelCase						=		['''BeitImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BeitForImageClassification''',
		    '''BeitForMaskedImageModeling''',
		    '''BeitForSemanticSegmentation''',
		    '''BeitModel''',
		    '''BeitPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''FlaxBeitForImageClassification''',
		    '''FlaxBeitForMaskedImageModeling''',
		    '''FlaxBeitModel''',
		    '''FlaxBeitPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_beit import BeitFeatureExtractor
				from .image_processing_beit import BeitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_beit import (
				    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BeitForImageClassification,
				    BeitForMaskedImageModeling,
				    BeitForSemanticSegmentation,
				    BeitModel,
				    BeitPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_beit import (
				    FlaxBeitForImageClassification,
				    FlaxBeitForMaskedImageModeling,
				    FlaxBeitModel,
				    FlaxBeitPreTrainedModel,
				)


else:
		import sys

		lowerCamelCase						=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




