




"""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							:		Optional[Any]								=  iter(snake_case__    )
  while True:
    _snake_case							:		List[str]								=  tuple(itertools.islice(snake_case__		,   snake_case__    )    )
    if not chunk:
      return
    yield chunk


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

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

  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							:		Dict								=  """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							:		List[Any]								=  []

  # 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							:		Optional[int]								=  generate_table(snake_case__    )
  _snake_case							:		Tuple								=  prepare_input(snake_case__    )
  _snake_case							:		int								=  """"""

  # https://en.wikipedia.org/wiki/Playfair_cipher#Description
  for chara, chara in chunker(snake_case__		,   2    ):
    _snake_case		,					_snake_case							:		int								=  divmod(table.index(snake_case__    )		,   5    )
    _snake_case		,					_snake_case							:		Dict								=  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							:		Union[str, Any]								=  generate_table(snake_case__    )
  _snake_case							:		List[Any]								=  """"""

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









import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


SCREAMING_SNAKE_CASE_						   =       logging.getLogger(__name__)

@dataclass
class 		UpperCamelCase__ (      lowerCAmelCase_   ):



     '''simple docstring'''

     __snake_case    :	Optional[float]			=			field(
         default=0.0							,      metadata={"help": "The label smoothing epsilon to apply (if not zero)."}   )
     __snake_case    :	bool			=			field(default=lowerCAmelCase_							,      metadata={"help": "Whether to SortishSamler or not."}   )
     __snake_case    :	bool			=			field(
         default=lowerCAmelCase_							,      metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}   )
     __snake_case    :	bool			=			field(default=lowerCAmelCase_							,      metadata={"help": "whether to use adafactor"}   )
     __snake_case    :	Optional[float]			=			field(
         default=lowerCAmelCase_							,      metadata={"help": "Encoder layer dropout probability. Goes into model.config."}   )
     __snake_case    :	Optional[float]			=			field(
         default=lowerCAmelCase_							,      metadata={"help": "Decoder layer dropout probability. Goes into model.config."}   )
     __snake_case    :	Optional[float]			=			field(default=lowerCAmelCase_							,      metadata={"help": "Dropout probability. Goes into model.config."}   )
     __snake_case    :	Optional[float]			=			field(
         default=lowerCAmelCase_							,      metadata={"help": "Attention dropout probability. Goes into model.config."}   )
     __snake_case    :	Optional[str]			=			field(
         default="linear"							,      metadata={"help": F"Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()   )}"}							,      )


