




'''simple docstring'''



from typing import TYPE_CHECKING

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


UpperCamelCase_    	=				{
    "configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBertOnnxConfig"],
    "tokenization_convbert": ["ConvBertTokenizer"],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_    	=				[
          "CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ConvBertForMaskedLM",
          "ConvBertForMultipleChoice",
          "ConvBertForQuestionAnswering",
          "ConvBertForSequenceClassification",
          "ConvBertForTokenClassification",
          "ConvBertLayer",
          "ConvBertModel",
          "ConvBertPreTrainedModel",
          "load_tf_weights_in_convbert",
      ]


try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_    	=				[
          "TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFConvBertForMaskedLM",
          "TFConvBertForMultipleChoice",
          "TFConvBertForQuestionAnswering",
          "TFConvBertForSequenceClassification",
          "TFConvBertForTokenClassification",
          "TFConvBertLayer",
          "TFConvBertModel",
          "TFConvBertPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
      from .tokenization_convbert import ConvBertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_convbert_fast import ConvBertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_convbert import (
                CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                ConvBertForMaskedLM,
                ConvBertForMultipleChoice,
                ConvBertForQuestionAnswering,
                ConvBertForSequenceClassification,
                ConvBertForTokenClassification,
                ConvBertLayer,
                ConvBertModel,
                ConvBertPreTrainedModel,
                load_tf_weights_in_convbert,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_convbert import (
                TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFConvBertForMaskedLM,
                TFConvBertForMultipleChoice,
                TFConvBertForQuestionAnswering,
                TFConvBertForSequenceClassification,
                TFConvBertForTokenClassification,
                TFConvBertLayer,
                TFConvBertModel,
                TFConvBertPreTrainedModel,
            )


else:
      import sys

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










import itertools
import string
from collections.abc import Generator, Iterable





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       iter(__snake_case							)
     while True:
          __lowerCAmelCase             =       tuple(itertools.islice(__snake_case       ,			__snake_case							)							)
          if not chunk:
               return
          yield chunk





def    __lowerCAmelCase   (    __snake_case							):
     __lowerCAmelCase             =       "".join([c.upper() for c in dirty if c in string.ascii_letters]							)
     __lowerCAmelCase             =       ""

     if len(__snake_case							) < 2:
          return dirty

     for i in range(len(__snake_case							) - 1							):
          clean += dirty[i]

          if dirty[i] == dirty[i + 1]:
               clean += "X"

     clean += dirty[-1]

     if len(__snake_case							) & 1:
          clean += "X"

     return clean





def    __lowerCAmelCase   (    __snake_case							):
     # I and J are used interchangeably to allow
     # us to use a 5x5 table (25 letters)
     __lowerCAmelCase             =       "ABCDEFGHIKLMNOPQRSTUVWXYZ"
     # we're using a list instead of a '2d' array because it makes the math
     # for setting up the table and doing the actual encoding/decoding simpler
     __lowerCAmelCase             =       []

     # copy key chars into the table if they are in `alphabet` ignoring duplicates
     for char in key.upper():
          if char not in table and char in alphabet:
               table.append(__snake_case							)

    # fill the rest of the table in with the remaining alphabet chars
     for char in alphabet:
          if char not in table:
               table.append(__snake_case							)

     return table





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       generate_table(__snake_case							)
     __lowerCAmelCase             =       prepare_input(__snake_case							)
     __lowerCAmelCase             =       ""

     # https://en.wikipedia.org/wiki/Playfair_cipher#Description
     for chara, chara in chunker(__snake_case       ,			2							):
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)

          if rowa == rowa:
               ciphertext += table[rowa * 5 + (cola + 1) % 5]
               ciphertext += table[rowa * 5 + (cola + 1) % 5]
          elif cola == cola:
               ciphertext += table[((rowa + 1) % 5) * 5 + cola]
               ciphertext += table[((rowa + 1) % 5) * 5 + cola]
          else:  # rectangle
               ciphertext += table[rowa * 5 + cola]
               ciphertext += table[rowa * 5 + cola]

     return ciphertext





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       generate_table(__snake_case							)
     __lowerCAmelCase             =       ""

     # https://en.wikipedia.org/wiki/Playfair_cipher#Description
     for chara, chara in chunker(__snake_case       ,			2							):
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)

          if rowa == rowa:
               plaintext += table[rowa * 5 + (cola - 1) % 5]
               plaintext += table[rowa * 5 + (cola - 1) % 5]
          elif cola == cola:
               plaintext += table[((rowa - 1) % 5) * 5 + cola]
               plaintext += table[((rowa - 1) % 5) * 5 + cola]
          else:  # rectangle
               plaintext += table[rowa * 5 + cola]
               plaintext += table[rowa * 5 + cola]

     return plaintext






