




"""simple docstring"""


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


def  UpperCAmelCase__	(snake_case__							: Iterable[str]		,       snake_case__							: int   ):
  """simple docstring"""

  _snake_case							:		Tuple								=  iter(snake_case__   )
  while True:
    _snake_case							:		Optional[int]								=  tuple(itertools.islice(snake_case__		,       snake_case__   )   )
    if not chunk:
      return
    yield chunk


def  UpperCAmelCase__	(snake_case__							: str   ):
  """simple docstring"""

  _snake_case							:		List[Any]								=  """""".join([c.upper() for c in dirty if c in string.ascii_letters]   )
  _snake_case							:		int								=  """"""

  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  UpperCAmelCase__	(snake_case__							: str   ):
  """simple docstring"""

  _snake_case							:		str								=  """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
  _snake_case							:		str								=  []

  # 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  UpperCAmelCase__	(snake_case__							: str		,       snake_case__							: str   ):
  """simple docstring"""

  _snake_case							:		List[Any]								=  generate_table(snake_case__   )
  _snake_case							:		List[Any]								=  prepare_input(snake_case__   )
  _snake_case							:		str								=  """"""

  # https://en.wikipedia.org/wiki/Playfair_cipher#Description
  for chara, chara in chunker(snake_case__		,       2   ):
    _snake_case		, _snake_case							:		Optional[Any]								=  divmod(table.index(snake_case__   )		,       5   )
    _snake_case		, _snake_case							:		Optional[Any]								=  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  UpperCAmelCase__	(snake_case__							: str		,       snake_case__							: str   ):
  """simple docstring"""

  _snake_case							:		Optional[Any]								=  generate_table(snake_case__   )
  _snake_case							:		Tuple								=  """"""

  # https://en.wikipedia.org/wiki/Playfair_cipher#Description
  for chara, chara in chunker(snake_case__		,       2   ):
    _snake_case		, _snake_case							:		Tuple								=  divmod(table.index(snake_case__   )		,       5   )
    _snake_case		, _snake_case							:		Optional[Any]								=  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








"""simple docstring"""


from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)


