
'''simple docstring'''







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







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			Generator[tuple[str, ...], None, None]:
	_snake_case     		=	iter(__A			)
	while True:
		_snake_case     		=	tuple(itertools.islice(__A    ,       __A			)			)
		if not chunk:
			return
		yield chunk







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			str:
	_snake_case     		=	''.join([c.upper() for c in dirty if c in string.ascii_letters]			)
	_snake_case     		=	''

	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        SCREAMING_SNAKE_CASE__			(     __A			) ->			list[str]:
	# I and J are used interchangeably to allow
	# us to use a 5x5 table (25 letters)
	_snake_case     		=	'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     		=	[]

	# 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        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			str:
	_snake_case     		=	generate_table(__A			)
	_snake_case     		=	prepare_input(__A			)
	_snake_case     		=	''

	# https://en.wikipedia.org/wiki/Playfair_cipher#Description
	for chara, chara in chunker(__A    ,       2			):
		_snake_case		,				_snake_case     		=	divmod(table.index(__A			)    ,       5			)
		_snake_case		,				_snake_case     		=	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        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			str:
	_snake_case     		=	generate_table(__A			)
	_snake_case     		=	''

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

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


lowercase					:							Optional[Any]   =      logging.get_logger(__name__)

lowercase					:							str   =      {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

lowercase					:							Optional[Any]   =      {
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

lowercase					:							List[Any]   =      {
    "facebook/blenderbot_small-90M": 512,
}


class 		__UpperCAmelCase   (      _lowerCamelCase		):
							__lowercase   	= VOCAB_FILES_NAMES
							__lowercase   	= PRETRAINED_VOCAB_FILES_MAP
							__lowercase   	= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase   	= BlenderbotSmallTokenizer


							def __init__( self					,     lowerCAmelCase_=None					,     lowerCAmelCase_=None					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_=False					,     lowerCAmelCase_=True					,     **lowerCAmelCase_					,     ):





								"""simple docstring"""






								super().__init__(
								    ByteLevelBPETokenizer(
								        vocab=lowerCAmelCase_					,     merges=lowerCAmelCase_					,     add_prefix_space=lowerCAmelCase_					,     trim_offsets=lowerCAmelCase_					,     )					,     bos_token=lowerCAmelCase_					,     eos_token=lowerCAmelCase_					,     unk_token=lowerCAmelCase_					,     **lowerCAmelCase_					,     )
								_snake_case     		=	add_prefix_space


							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_=None						):





								"""simple docstring"""






								_snake_case     		=	[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_ = None						):





								"""simple docstring"""






								_snake_case     		=	[self.sep_token_id]
								_snake_case     		=	[self.cls_token_id]

								if token_ids_a is None:
									return len(cls + token_ids_a + sep						) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep						) * [0]

