





import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs


class     A     (SCREAMING_SNAKE_CASE       ):
			'''simple docstring'''




			def __init__(     self  :       Any				,      __lowerCAmelCase  :       Optional[int]				,      __lowerCAmelCase  :       int=None				,      __lowerCAmelCase  :       Tuple=True				,      __lowerCAmelCase  :       Any=None				,      **__lowerCAmelCase  :       Dict  )      ->      Optional[Any]:







					"""simple docstring"""






					A__     =  parent
					A__     =  config_class
					A__     =  has_text_modality
					A__     =  kwargs
					A__     =  common_properties






			def   a_			(     self  :       Optional[int]  )      ->      int:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict  )
					A__     =  (
					    ["""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(__lowerCAmelCase				,      __lowerCAmelCase  )				,      msg=f'`{prop}` does not exist'  )

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






			def   a_			(     self  :       int  )      ->      str:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict  )
					A__     =  json.loads(config.to_json_string()  )
					for key, value in self.inputs_dict.items():
							self.parent.assertEqual(obj[key]				,      __lowerCAmelCase  )






			def   a_			(     self  :       Union[str, Any]  )      ->      int:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict  )

					with tempfile.TemporaryDirectory() as tmpdirname:
							A__     =  os.path.join(__lowerCAmelCase				,      """config.json"""  )
							config_first.to_json_file(__lowerCAmelCase  )
							A__     =  self.config_class.from_json_file(__lowerCAmelCase  )

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






			def   a_			(     self  :       Optional[Any]  )      ->      Optional[Any]:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict  )

					with tempfile.TemporaryDirectory() as tmpdirname:
							config_first.save_pretrained(__lowerCAmelCase  )
							A__     =  self.config_class.from_pretrained(__lowerCAmelCase  )

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






			def   a_			(     self  :       Union[str, Any]  )      ->      Optional[int]:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict  )

					A__     =  """test"""
					with tempfile.TemporaryDirectory() as tmpdirname:
							A__     =  os.path.join(__lowerCAmelCase				,      __lowerCAmelCase  )
							config_first.save_pretrained(__lowerCAmelCase  )
							A__     =  self.config_class.from_pretrained(__lowerCAmelCase				,      subfolder=__lowerCAmelCase  )

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






			def   a_			(     self  :       List[str]  )      ->      Dict:







					"""simple docstring"""






					A__     =  self.config_class(**self.inputs_dict				,      num_labels=5  )
					self.parent.assertEqual(len(config.idalabel  )				,      5  )
					self.parent.assertEqual(len(config.labelaid  )				,      5  )

					A__     =  3
					self.parent.assertEqual(len(config.idalabel  )				,      3  )
					self.parent.assertEqual(len(config.labelaid  )				,      3  )






			def   a_			(     self  :       Any  )      ->      Dict:







					"""simple docstring"""






					if self.config_class.is_composition:
							return
					A__     =  self.config_class()
					self.parent.assertIsNotNone(__lowerCAmelCase  )






			def   a_			(     self  :       Optional[Any]  )      ->      str:







					"""simple docstring"""






					A__     =  copy.deepcopy(__lowerCAmelCase  )
					A__     =  self.config_class(**__lowerCAmelCase  )
					A__     =  []
					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(__lowerCAmelCase				,      __lowerCAmelCase  ) != value:
									wrong_values.append((key, getattr(__lowerCAmelCase				,      __lowerCAmelCase  ), value)  )

					if len(__lowerCAmelCase  ) > 0:
							A__     =  """\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   a_			(     self  :       int  )      ->      List[str]:







					"""simple docstring"""






					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_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


A       :   Dict					= {'''processing_layoutxlm''': ['''LayoutXLMProcessor''']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Dict					= ['''LayoutXLMTokenizer''']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Dict					= ['''LayoutXLMTokenizerFast''']

if TYPE_CHECKING:
					from .processing_layoutxlm import LayoutXLMProcessor

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutxlm import LayoutXLMTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
					import sys

					A       :   int					= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



