
from typing import TYPE_CHECKING

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


lowercase__          ={
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__          =['LayoutLMv2TokenizerFast']

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__          =['LayoutLMv2FeatureExtractor']
      lowercase__          =['LayoutLMv2ImageProcessor']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__          =[
          'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
          'LayoutLMv2ForQuestionAnswering',
          'LayoutLMv2ForSequenceClassification',
          'LayoutLMv2ForTokenClassification',
          'LayoutLMv2Layer',
          'LayoutLMv2Model',
          'LayoutLMv2PreTrainedModel',
      ]

if TYPE_CHECKING:
      from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaLayer,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )
else:
      import sys

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


def        __UpperCamelCase					(    lowerCAmelCase__							:    list[list[int | float]]  ):
 __a			:  int		    =  len(lowerCAmelCase__  )
 __a			:  Dict		    =  len(matrix[0]  )
 __a			:  Union[str, Any]		    =  min(lowerCAmelCase__  ,       lowerCAmelCase__  )

 for row in range(lowerCAmelCase__  ):
  # Check if diagonal element is not zero
  if matrix[row][row] != 0:
   # Eliminate all the elements below the diagonal
   for col in range(row + 1  ,       lowerCAmelCase__  ):
    __a			:  Dict		    =  matrix[col][row] / matrix[row][row]
    for i in range(lowerCAmelCase__  ,       lowerCAmelCase__  ):
     matrix[col][i] -= multiplier * matrix[row][i]
  else:
   # Find a non-zero diagonal element to swap rows
   __a			:  Optional[int]		    =  True
   for i in range(row + 1  ,       lowerCAmelCase__  ):
    if matrix[i][row] != 0:
     __a    ,	__a			:  Any		    =  matrix[i], matrix[row]
     __a			:  Union[str, Any]		    =  False
     break
   if reduce:
    rank -= 1
    for i in range(lowerCAmelCase__  ):
     __a			:  Optional[Any]		    =  matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
   row -= 1

 return rank


if __name__ == "__main__":
      import doctest

      doctest.testmod()
