




from typing import TYPE_CHECKING

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


a_ 		=  {
    "configuration_layoutlm": ["LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMConfig", "LayoutLMOnnxConfig"],
    "tokenization_layoutlm": ["LayoutLMTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_ 		=  ["LayoutLMTokenizerFast"]

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

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_ 		=  [
     "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

 a_ 		=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







"""simple docstring"""







def   __lowerCAmelCase(		__UpperCAmelCase      ):






	"""simple docstring"""





	if len(__UpperCAmelCase      ) > 1:
		_lowercase			:     Dict      					=				len(__UpperCAmelCase      ) // 2  # Finds the middle of the array
		_lowercase			:     List[str]      					=				arr[
		    :middle_length
		]  # Creates an array of the elements in the first half.
		_lowercase			:     Optional[int]      					=				arr[
		    middle_length:
		]  # Creates an array of the elements in the second half.
		_lowercase			:     Optional[Any]      					=				len(__UpperCAmelCase      )
		_lowercase			:     Optional[int]      					=				len(__UpperCAmelCase      )
		merge(__UpperCAmelCase      )  # Starts sorting the left.
		merge(__UpperCAmelCase      )  # Starts sorting the right
		_lowercase			:     Dict      					=				0  # Left Counter
		_lowercase			:     List[str]      					=				0  # Right Counter
		_lowercase			:     Optional[Any]      					=				0  # Position Counter
		while (
		    left_index < left_size and right_index < right_size
		):  # Runs until the lowers size of the left and right are sorted.
			if left_array[left_index] < right_array[right_index]:
				_lowercase			:     Optional[int]      					=				left_array[left_index]
				left_index += 1
			else:
				_lowercase			:     int      					=				right_array[right_index]
				right_index += 1
			index += 1
		while (
		    left_index < left_size
		):  # Adds the left over elements in the left half of the array
			_lowercase			:     Any      					=				left_array[left_index]
			left_index += 1
			index += 1
		while (
		    right_index < right_size
		):  # Adds the left over elements in the right half of the array
			_lowercase			:     str      					=				right_array[right_index]
			right_index += 1
			index += 1
	return arr


if __name__ == "__main__":
						import doctest

						doctest.testmod()



