


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase			:					Optional[int]         =							{
    """configuration_layoutlm""": ["""LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMConfig""", """LayoutLMOnnxConfig"""],
    """tokenization_layoutlm""": ["""LayoutLMTokenizer"""],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					Union[str, Any]         =							["""LayoutLMTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					List[str]         =							[
					    """LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """LayoutLMForMaskedLM""",
					    """LayoutLMForSequenceClassification""",
					    """LayoutLMForTokenClassification""",
					    """LayoutLMForQuestionAnswering""",
					    """LayoutLMModel""",
					    """LayoutLMPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					Tuple         =							[
					    """TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFLayoutLMForMaskedLM""",
					    """TFLayoutLMForSequenceClassification""",
					    """TFLayoutLMForTokenClassification""",
					    """TFLayoutLMForQuestionAnswering""",
					    """TFLayoutLMMainLayer""",
					    """TFLayoutLMModel""",
					    """TFLayoutLMPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
					from .tokenization_layoutlm import LayoutLMTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_layoutlm import (
										    LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LayoutLMForMaskedLM,
										    LayoutLMForQuestionAnswering,
										    LayoutLMForSequenceClassification,
										    LayoutLMForTokenClassification,
										    LayoutLMModel,
										    LayoutLMPreTrainedModel,
										)
					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_layoutlm import (
										    TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFLayoutLMForMaskedLM,
										    TFLayoutLMForQuestionAnswering,
										    TFLayoutLMForSequenceClassification,
										    TFLayoutLMForTokenClassification,
										    TFLayoutLMMainLayer,
										    TFLayoutLMModel,
										    TFLayoutLMPreTrainedModel,
										)

else:
					import sys

					UpperCamelCase			:					Tuple         =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






class lowerCAmelCase_       :







	'''simple docstring'''




	def __init__(	self   ,       lowerCamelCase=None       ):



				'''simple docstring'''


				a__					=  data
				a__					=  None







	def __repr__(	self       ):



				'''simple docstring'''


				a__					=  """"""
				a__					=  self
				while temp:
							string_rep += f'<{temp.data}> ---> '
							a__					=  temp.next
				string_rep += "<END>"
				return string_rep




def    UpperCAmelCase					(  lowercase__						:					Optional[int]	):



			'''simple docstring'''





			if not elements_list:
						raise Exception("""The Elements List is empty"""	)

			# Set first element as Head
			a__					=  Node(elements_list[0]	)
			a__					=  head
			# Loop through elements from position 1
			for data in elements_list[1:]:
						a__					=  Node(lowercase__	)
						a__					=  current.next
			return head


_lowercase				:					List[Any]     					=[1, 3, 5, 32, 44, 12, 43]
print(f'''List: {list_data}''')
print("""Creating Linked List from List.""")
_lowercase				:					Dict     					=make_linked_list(list_data)
print("""Linked List:""")





print(linked_list)

