


__UpperCamelCase    :						Optional[Any]     =							256
# Modulus to hash a string
__UpperCamelCase    :						Any     =							1000003





def   _UpperCAmelCase       (     UpperCAmelCase      :			str						,	UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      str       						=						len(UpperCAmelCase      )
      __lowerCamelCase     :      List[Any]       						=						len(UpperCAmelCase      )
      if p_len > t_len:
            return False

      __lowerCamelCase     :      List[Any]       						=						0
      __lowerCamelCase     :      str       						=						0
      __lowerCamelCase     :      Any       						=						1

      # Calculating the hash of pattern and substring of text
      for i in range(UpperCAmelCase      ):
            __lowerCamelCase     :      Dict       						=						(ord(pattern[i]      ) + p_hash * alphabet_size) % modulus
            __lowerCamelCase     :      List[Any]       						=						(ord(text[i]      ) + text_hash * alphabet_size) % modulus
            if i == p_len - 1:
                  continue
            __lowerCamelCase     :      Dict       						=						(modulus_power * alphabet_size) % modulus

      for i in range(0						,	t_len - p_len + 1      ):
            if text_hash == p_hash and text[i : i + p_len] == pattern:
                  return True
            if i == t_len - p_len:
                  continue
            # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
            __lowerCamelCase     :      List[str]       						=						(
                (text_hash - ord(text[i]      ) * modulus_power) * alphabet_size
                + ord(text[i + p_len]      )
            ) % modulus
      return False





def   _UpperCAmelCase       (     ):
      """simple docstring"""




      __lowerCamelCase     :      List[Any]       						=						"""abc1abc12"""
      __lowerCamelCase     :      Dict       						=						"""alskfjaldsabc1abc1abc12k23adsfabcabc"""
      __lowerCamelCase     :      int       						=						"""alskfjaldsk23adsfabcabc"""
      assert rabin_karp(UpperCAmelCase						,	UpperCAmelCase      ) and not rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )

      # Test 2)
      __lowerCamelCase     :      Optional[int]       						=						"""ABABX"""
      __lowerCamelCase     :      Tuple       						=						"""ABABZABABYABABX"""
      assert rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )

      # Test 3)
      __lowerCamelCase     :      Dict       						=						"""AAAB"""
      __lowerCamelCase     :      str       						=						"""ABAAAAAB"""
      assert rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )

      # Test 4)
      __lowerCamelCase     :      str       						=						"""abcdabcy"""
      __lowerCamelCase     :      Any       						=						"""abcxabcdabxabcdabcdabcy"""
      assert rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )

      # Test 5)
      __lowerCamelCase     :      List[Any]       						=						"""Lü"""
      __lowerCamelCase     :      Tuple       						=						"""Lüsai"""
      assert rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )
      __lowerCamelCase     :      str       						=						"""Lue"""
      assert not rabin_karp(UpperCAmelCase						,	UpperCAmelCase      )
      print("""Success."""      )


if __name__ == "__main__":
    test_rabin_karp()







from typing import TYPE_CHECKING

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


__UpperCamelCase    :						Union[str, Any]     =							{
    '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:
    __UpperCamelCase    :						List[str]     =							['LayoutLMv2TokenizerFast']

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						List[str]     =							['LayoutLMv2FeatureExtractor']
    __UpperCamelCase    :						Union[str, Any]     =							['LayoutLMv2ImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						Dict     =							[
        '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

    __UpperCamelCase    :						Optional[Any]     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



