



"""simple docstring"""

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




def __lowercase    (							_a	,    _a					):
    snake_case_				:  List[Any]       =			iter(_a					)
    while True:
        snake_case_				:  List[Any]       =			tuple(itertools.islice(_a	,    _a					)					)
        if not chunk:
            return
        yield chunk




def __lowercase    (							_a					):
    snake_case_				:  Optional[Any]       =			''''''.join([c.upper() for c in dirty if c in string.ascii_letters]					)
    snake_case_				:  Tuple       =			''''''

    if len(_a					) < 2:
        return dirty

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

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

    clean += dirty[-1]

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

    return clean




def __lowercase    (							_a					):
    # I and J are used interchangeably to allow
    # us to use a 5x5 table (25 letters)
    snake_case_				:  Any       =			'''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_				:  Tuple       =			[]

    # 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(_a					)

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

    return table




def __lowercase    (							_a	,    _a					):
    snake_case_				:  Dict       =			generate_table(_a					)
    snake_case_				:  Dict       =			prepare_input(_a					)
    snake_case_				:  str       =			''''''

    # https://en.wikipedia.org/wiki/Playfair_cipher#Description
    for chara, chara in chunker(_a	,    2					):
        snake_case_,			snake_case_				:  Optional[Any]       =			divmod(table.index(_a					)	,    5					)
        snake_case_,			snake_case_				:  Any       =			divmod(table.index(_a					)	,    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 __lowercase    (							_a	,    _a					):
    snake_case_				:  str       =			generate_table(_a					)
    snake_case_				:  Optional[int]       =			''''''

    # https://en.wikipedia.org/wiki/Playfair_cipher#Description
    for chara, chara in chunker(_a	,    2					):
        snake_case_,			snake_case_				:  Optional[Any]       =			divmod(table.index(_a					)	,    5					)
        snake_case_,			snake_case_				:  Optional[Any]       =			divmod(table.index(_a					)	,    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 typing import TYPE_CHECKING

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


lowercase__					:						List[Any]												=			{'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						List[Any]												=			['''XGLMTokenizer''']

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

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						Tuple												=			[
         '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''XGLMForCausalLM''',
         '''XGLMModel''',
         '''XGLMPreTrainedModel''',
     ]


try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						int												=			[
         '''FlaxXGLMForCausalLM''',
         '''FlaxXGLMModel''',
         '''FlaxXGLMPreTrainedModel''',
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						Tuple												=			[
         '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFXGLMForCausalLM''',
         '''TFXGLMModel''',
         '''TFXGLMPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_xglm import XGLMTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_xglm_fast import XGLMTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_xglm import (
              TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFXGLMForCausalLM,
              TFXGLMModel,
              TFXGLMPreTrainedModel,
          )


else:
     import sys

     lowercase__					:						List[Any]												=			_LazyModule(__name__, globals()['''__file__'''], _import_structure)





