

"""simple docstring"""


import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
			from transformers.pipelines.conversational import Conversation

__A						   =			logging.get_logger(__name__)


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

__A						   =			{
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

__A						   =			{"facebook/blenderbot-3B": 128}






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def     a__    (    )	->	Optional[int]:
		__lowerCAmelCase:       List[Any]          =			(
		    list(range(ord("!" )					, ord("~" ) + 1 ) ) + list(range(ord("¡" )					, ord("¬" ) + 1 ) ) + list(range(ord("®" )					, ord("ÿ" ) + 1 ) )
		)
		__lowerCAmelCase:       List[str]          =			bs[:]
		__lowerCAmelCase:       List[str]          =			0
		for b in range(2**8 ):
				if b not in bs:
						bs.append(__SCREAMING_SNAKE_CASE )
						cs.append(2**8 + n )
						n += 1
		__lowerCAmelCase:       Any          =			[chr(__SCREAMING_SNAKE_CASE ) for n in cs]
		return dict(zip(__SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE ) )






def     a__    (    __SCREAMING_SNAKE_CASE )	->	Any:
		__lowerCAmelCase:       Dict          =			set()
		__lowerCAmelCase:       List[Any]          =			word[0]
		for char in word[1:]:
				pairs.add((prev_char, char) )
				__lowerCAmelCase:       List[str]          =			char
		return pairs





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      str         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      List[Any]         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Any         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  ["""input_ids""", """attention_mask"""]

				def __init__(	self							:				Dict     ,  UpperCamelCase__							:				Union[str, Any]     ,  UpperCamelCase__							:				Union[str, Any]     ,  UpperCamelCase__							:				Optional[int]="replace"     ,  UpperCamelCase__							:				List[Any]="<s>"     ,  UpperCamelCase__							:				List[str]="</s>"     ,  UpperCamelCase__							:				Union[str, Any]="</s>"     ,  UpperCamelCase__							:				Optional[int]="<s>"     ,  UpperCamelCase__							:				Optional[int]="<unk>"     ,  UpperCamelCase__							:				Dict="<pad>"     ,  UpperCamelCase__							:				Optional[Any]="<mask>"     ,  UpperCamelCase__							:				Union[str, Any]=False     ,  **UpperCamelCase__							:				Optional[Any]     ,  )->   Dict:



						'''simple docstring'''


						__lowerCAmelCase:       Union[str, Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else bos_token
						__lowerCAmelCase:       Dict          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else eos_token
						__lowerCAmelCase:       List[Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else sep_token
						__lowerCAmelCase:       Union[str, Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else cls_token
						__lowerCAmelCase:       List[str]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else unk_token
						__lowerCAmelCase:       List[Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else pad_token

						# Mask token behave like a normal word, i.e. include the space before it
						__lowerCAmelCase:       Union[str, Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else mask_token

						super().__init__(
						    errors=UpperCamelCase__     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  add_prefix_space=UpperCamelCase__     ,  **UpperCamelCase__     ,  )

						with open(UpperCamelCase__     ,  encoding="utf-8") as vocab_handle:
								__lowerCAmelCase:       Tuple          =			json.load(UpperCamelCase__)
						__lowerCAmelCase:       Optional[int]          =			{v: k for k, v in self.encoder.items()}
						__lowerCAmelCase:       Optional[Any]          =			errors  # how to handle errors in decoding
						__lowerCAmelCase:       Optional[int]          =			bytes_to_unicode()
						__lowerCAmelCase:       int          =			{v: k for k, v in self.byte_encoder.items()}
						with open(UpperCamelCase__     ,  encoding="utf-8") as merges_handle:
								__lowerCAmelCase:       Union[str, Any]          =			merges_handle.read().split("\n")[1:-1]
						__lowerCAmelCase:       Dict          =			[tuple(merge.split()) for merge in bpe_merges]
						__lowerCAmelCase:       Union[str, Any]          =			dict(zip(UpperCamelCase__     ,  range(len(UpperCamelCase__))))
						__lowerCAmelCase:       Dict          =			{}
						__lowerCAmelCase:       int          =			add_prefix_space

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						__lowerCAmelCase:       Dict          =			re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+")

				@property
				# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
				def 							lowercase_     (	self							:				Optional[Any])->   List[Any]:



						'''simple docstring'''


						return len(self.encoder)

				def 							lowercase_     (	self							:				Optional[int])->   Union[str, Any]:



						'''simple docstring'''


						return dict(self.encoder     ,  **self.added_tokens_encoder)

				def 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				List[str])->   Tuple:



						'''simple docstring'''


						if token in self.cache:
								return self.cache[token]
						__lowerCAmelCase:       int          =			tuple(UpperCamelCase__)
						__lowerCAmelCase:       Union[str, Any]          =			get_pairs(UpperCamelCase__)

						if not pairs:
								return token

						while True:
								__lowerCAmelCase:       Any          =			min(UpperCamelCase__     ,  key=lambda UpperCamelCase__: self.bpe_ranks.get(UpperCamelCase__     ,  float("inf")))
								if bigram not in self.bpe_ranks:
										break
								__lowerCAmelCase      , __lowerCAmelCase:       Tuple          =			bigram
								__lowerCAmelCase:       int          =			[]
								__lowerCAmelCase:       Any          =			0
								while i < len(UpperCamelCase__):
										try:
												__lowerCAmelCase:       int          =			word.index(UpperCamelCase__     ,  UpperCamelCase__)
										except ValueError:
												new_word.extend(word[i:])
												break
										else:
												new_word.extend(word[i:j])
												__lowerCAmelCase:       List[str]          =			j

										if word[i] == first and i < len(UpperCamelCase__) - 1 and word[i + 1] == second:
												new_word.append(first + second)
												i += 2
										else:
												new_word.append(word[i])
												i += 1
								__lowerCAmelCase:       List[str]          =			tuple(UpperCamelCase__)
								__lowerCAmelCase:       Optional[int]          =			new_word
								if len(UpperCamelCase__) == 1:
										break
								else:
										__lowerCAmelCase:       Any          =			get_pairs(UpperCamelCase__)
						__lowerCAmelCase:       str          =			" ".join(UpperCamelCase__)
						__lowerCAmelCase:       List[Any]          =			word
						return word

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Any)->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Any          =			[]
						for token in re.findall(self.pat     ,  UpperCamelCase__):
								__lowerCAmelCase:       Tuple          =			"".join(
								    self.byte_encoder[b] for b in token.encode("utf-8"))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
								bpe_tokens.extend(bpe_token for bpe_token in self.bpe(UpperCamelCase__).split(" "))
						return bpe_tokens

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				Optional[int])->   Optional[int]:



						'''simple docstring'''


						return self.encoder.get(UpperCamelCase__     ,  self.encoder.get(self.unk_token))

				def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				int)->   Union[str, Any]:



						'''simple docstring'''


						return self.decoder.get(UpperCamelCase__)

				def 							lowercase_     (	self							:				Tuple     ,  UpperCamelCase__							:				Optional[Any])->   Any:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			"".join(UpperCamelCase__)
						__lowerCAmelCase:       str          =			bytearray([self.byte_decoder[c] for c in text]).decode("utf-8"     ,  errors=self.errors)
						return text

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						if not os.path.isdir(UpperCamelCase__):
								logger.error(f"Vocabulary path ({save_directory}) should be a directory")
								return
						__lowerCAmelCase:       Any          =			os.path.join(
						    UpperCamelCase__     ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])
						__lowerCAmelCase:       Any          =			os.path.join(
						    UpperCamelCase__     ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"])

						with open(UpperCamelCase__     ,  "w"     ,  encoding="utf-8") as f:
								f.write(json.dumps(self.encoder     ,  indent=2     ,  sort_keys=UpperCamelCase__     ,  ensure_ascii=UpperCamelCase__) + "\n")

						__lowerCAmelCase:       Dict          =			0
						with open(UpperCamelCase__     ,  "w"     ,  encoding="utf-8") as writer:
								writer.write("#version: 0.2\n")
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,  key=lambda UpperCamelCase__: kv[1]):
										if index != token_index:
												logger.warning(
												    f"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
												    " Please check that the tokenizer is not corrupted!")
												__lowerCAmelCase:       Dict          =			token_index
										writer.write(" ".join(UpperCamelCase__) + "\n")
										index += 1

						return vocab_file, merge_file

				def 							lowercase_     (	self							:				List[Any]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None     ,  UpperCamelCase__							:				bool = False)->   List[int]:



						'''simple docstring'''


						if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=UpperCamelCase__     ,  token_ids_a=UpperCamelCase__     ,  already_has_special_tokens=UpperCamelCase__)

						if token_ids_a is None:
								return [1] + ([0] * len(UpperCamelCase__)) + [1]
						return [1] + ([0] * len(UpperCamelCase__)) + [1, 1] + ([0] * len(UpperCamelCase__)) + [1]

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			[self.sep_token_id]
						__lowerCAmelCase:       Optional[int]          =			[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]

				def 							lowercase_     (	self							:				Tuple     ,  UpperCamelCase__							:				Dict     ,  UpperCamelCase__							:				Union[str, Any]=False     ,  **UpperCamelCase__							:				str)->   Tuple:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			kwargs.pop("add_prefix_space"     ,  self.add_prefix_space)
						if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase__) > 0 and not text[0].isspace()):
								__lowerCAmelCase:       List[str]          =			" " + text
						return (text, kwargs)

				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[Any]:



						'''simple docstring'''


						return token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				Dict     ,  UpperCamelCase__							:				"Conversation")->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			[]
						for is_user, text in conversation.iter_texts():
								if is_user:
										# We need to space prefix as it's being done within blenderbot
										inputs.append(" " + text)
								else:
										# Generated responses should contain them already.
										inputs.append(UpperCamelCase__)

						__lowerCAmelCase:       Union[str, Any]          =			"  ".join(UpperCamelCase__)
						__lowerCAmelCase:       Optional[Any]          =			self.encode(UpperCamelCase__)
						if len(UpperCamelCase__) > self.model_max_length:
								__lowerCAmelCase:       Optional[int]          =			input_ids[-self.model_max_length :]
								logger.warning(f"Trimmed input from conversation as it was longer than {self.model_max_length} tokens.")
						return input_ids





"""simple docstring"""


import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
			from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
			__A						   =			get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
			from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__A						   =			128022
__A						   =			128028





@require_sentencepiece
class     snake_case	(				__snake_case,							unittest.TestCase  ):
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  MaMaaaTokenizer
				SCREAMING_SNAKE_CASE_   :      Tuple         =  False
				SCREAMING_SNAKE_CASE_   :      str         =  False
				SCREAMING_SNAKE_CASE_   :      List[str]         =  True

				def 							lowercase_     (	self							:				List[str])->   str:



						'''simple docstring'''


						super().setUp()

						__lowerCAmelCase:       List[str]          =			["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
						__lowerCAmelCase:       List[str]          =			dict(zip(UpperCamelCase__     ,  range(len(UpperCamelCase__))))
						__lowerCAmelCase:       Optional[Any]          =			Path(self.tmpdirname)
						save_json(UpperCamelCase__     ,  save_dir / VOCAB_FILES_NAMES["vocab_file"])
						if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
								copyfile(UpperCamelCase__     ,  save_dir / VOCAB_FILES_NAMES["spm_file"])

						__lowerCAmelCase:       Optional[int]          =			MaMaaaTokenizer.from_pretrained(self.tmpdirname)
						tokenizer.save_pretrained(self.tmpdirname)

				def 							lowercase_     (	self							:				Optional[int]     ,  **UpperCamelCase__							:				Union[str, Any])->   Optional[int]:



						'''simple docstring'''


						return MaMaaaTokenizer.from_pretrained(self.tmpdirname     ,  **UpperCamelCase__)

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				str)->   List[Any]:



						'''simple docstring'''


						return (
						    "This is a test",
						    "This is a test",
						)

				def 							lowercase_     (	self							:				Union[str, Any])->   str:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			"</s>"
						__lowerCAmelCase:       Dict          =			0

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase__)     ,  UpperCamelCase__)
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase__)     ,  UpperCamelCase__)

				def 							lowercase_     (	self							:				str)->   Dict:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			self.get_tokenizer()
						__lowerCAmelCase:       int          =			list(tokenizer.get_vocab().keys())

						self.assertEqual(vocab_keys[0]     ,  "</s>")
						self.assertEqual(vocab_keys[1]     ,  "<unk>")
						self.assertEqual(vocab_keys[-1]     ,  "<s>")
						self.assertEqual(len(UpperCamelCase__)     ,  tokenizer.vocab_size + len(tokenizer.get_added_vocab()))

				@unittest.skip("Skip this test while all models are still to be uploaded.")
				def 							lowercase_     (	self							:				Optional[Any])->   Any:



						'''simple docstring'''


						pass

				def 							lowercase_     (	self							:				Optional[int])->   List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			self.get_tokenizer()

						__lowerCAmelCase:       str          =			tokenizer.tokenize("This is a test")
						self.assertListEqual(UpperCamelCase__     ,  ["▁This", "▁is", "▁a", "▁t", "est"])

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(UpperCamelCase__)     ,  [2, 3, 4, 5, 6]     ,  )

						__lowerCAmelCase:       Union[str, Any]          =			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6])
						self.assertListEqual(UpperCamelCase__     ,  ["▁This", "▁is", "▁a", "▁t", "est"])

						__lowerCAmelCase:       Tuple          =			tokenizer.convert_tokens_to_string(UpperCamelCase__)
						self.assertEqual(UpperCamelCase__     ,  "This is a test")




				@slow
				def 							lowercase_     (	self							:				Optional[int])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Union[str, Any]          =			{"input_ids": [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=UpperCamelCase__     ,  model_name="facebook/m2m100_418M"     ,  revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"     ,  )





@require_torch
@require_sentencepiece
@require_tokenizers
class     snake_case	(				unittest.TestCase  ):
				SCREAMING_SNAKE_CASE_   :      List[str]         =  """facebook/m2m100_418M"""
				SCREAMING_SNAKE_CASE_   :      List[str]         =  [
				    """In my opinion, there are two levels of response from the French government.""",
				    """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
				]
				SCREAMING_SNAKE_CASE_   :      Tuple         =  [
				    """Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.""",
				    """L'affaire NSA souligne l'absence totale de débat sur le renseignement""",
				]

				# fmt: off
				SCREAMING_SNAKE_CASE_   :      Any         =  [EN_CODE, 5_93, 19_49, 11_57_81, 4, 7_15_86, 42_34, 6_06_33, 12_62_33, 4_32, 12_38_08, 1_55_92, 11_97, 11_71_32, 12_06_18, 5, 2]

				@classmethod
				def 							lowercase_     (	cls							:				int)->   str:



						'''simple docstring'''


						__lowerCAmelCase:       MaMaaaTokenizer          =			MaMaaaTokenizer.from_pretrained(
						    cls.checkpoint_name     ,  src_lang="en"     ,  tgt_lang="fr")
						__lowerCAmelCase:       Any          =			1
						return cls

				def 							lowercase_     (	self							:				int)->   Optional[int]:



						'''simple docstring'''


						self.assertEqual(self.tokenizer.get_lang_id("ar")     ,  1_2_8_0_0_6)
						self.assertEqual(self.tokenizer.get_lang_id("en")     ,  1_2_8_0_2_2)
						self.assertEqual(self.tokenizer.get_lang_id("ro")     ,  1_2_8_0_7_6)
						self.assertEqual(self.tokenizer.get_lang_id("mr")     ,  1_2_8_0_6_3)

				def 							lowercase_     (	self							:				int)->   int:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			self.tokenizer.get_vocab()
						self.assertEqual(len(UpperCamelCase__)     ,  self.tokenizer.vocab_size)
						self.assertEqual(vocab["<unk>"]     ,  3)
						self.assertIn(self.tokenizer.get_lang_token("en")     ,  UpperCamelCase__)

				def 							lowercase_     (	self							:				Optional[int])->   Dict:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			"en"
						__lowerCAmelCase:       Union[str, Any]          =			self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
						self.assertListEqual(self.expected_src_tokens     ,  UpperCamelCase__)

				def 							lowercase_     (	self							:				str)->   Tuple:



						'''simple docstring'''


						self.assertIn(UpperCamelCase__     ,  self.tokenizer.all_special_ids)
						# fmt: off
						__lowerCAmelCase:       Optional[Any]          =			[FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
						# fmt: on
						__lowerCAmelCase:       Optional[Any]          =			self.tokenizer.decode(UpperCamelCase__     ,  skip_special_tokens=UpperCamelCase__)
						__lowerCAmelCase:       List[Any]          =			self.tokenizer.decode(generated_ids[1:]     ,  skip_special_tokens=UpperCamelCase__)
						self.assertEqual(UpperCamelCase__     ,  UpperCamelCase__)
						self.assertNotIn(self.tokenizer.eos_token     ,  UpperCamelCase__)

				def 							lowercase_     (	self							:				Any)->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			tempfile.mkdtemp()
						__lowerCAmelCase:       Union[str, Any]          =			self.tokenizer.lang_token_to_id
						self.tokenizer.save_pretrained(UpperCamelCase__)
						__lowerCAmelCase:       Tuple          =			MaMaaaTokenizer.from_pretrained(UpperCamelCase__)
						self.assertDictEqual(new_tok.lang_token_to_id     ,  UpperCamelCase__)

				@require_torch
				def 							lowercase_     (	self							:				List[str])->   str:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			"en"
						__lowerCAmelCase:       str          =			"fr"

						__lowerCAmelCase:       Optional[int]          =			self.tokenizer(self.src_text     ,  text_target=self.tgt_text     ,  padding=UpperCamelCase__     ,  return_tensors="pt")

						__lowerCAmelCase:       Optional[Any]          =			shift_tokens_right(
						    batch["labels"]     ,  self.tokenizer.pad_token_id     ,  self.tokenizer.eos_token_id)

						for k in batch:
								__lowerCAmelCase:       Tuple          =			batch[k].tolist()
						# batch = {k: v.tolist() for k,v in batch.items()}
						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						# batch.decoder_inputs_ids[0][0] ==
						assert batch.input_ids[1][0] == EN_CODE
						assert batch.input_ids[1][-1] == 2
						assert batch.labels[1][0] == FR_CODE
						assert batch.labels[1][-1] == 2
						assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]

				@require_torch
				def 							lowercase_     (	self							:				Dict)->   Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			"mr"
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id("mr")])
						self.assertListEqual(self.tokenizer.suffix_tokens     ,  [self.tokenizer.eos_token_id])

						__lowerCAmelCase:       List[Any]          =			"zh"
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id("zh")])
						self.assertListEqual(self.tokenizer.suffix_tokens     ,  [self.tokenizer.eos_token_id])

				@require_torch
				def 							lowercase_     (	self							:				Optional[int])->   Any:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			"mr"
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id("mr")])
						self.assertListEqual(self.tokenizer.suffix_tokens     ,  [self.tokenizer.eos_token_id])
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang)])

						__lowerCAmelCase:       List[str]          =			"zh"
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id("zh")])
						self.assertListEqual(self.tokenizer.suffix_tokens     ,  [self.tokenizer.eos_token_id])
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens     ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang)])




				@require_torch
				def 							lowercase_     (	self							:				Union[str, Any])->   Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			self.tokenizer._build_translation_inputs("A test"     ,  return_tensors="pt"     ,  src_lang="en"     ,  tgt_lang="ar")

						self.assertEqual(
						    nested_simplify(UpperCamelCase__)     ,  {
						        # en_XX, A, test, EOS
						        "input_ids": [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
						        "attention_mask": [[1, 1, 1, 1]],
						        # ar_AR
						        "forced_bos_token_id": 1_2_8_0_0_6,
						    }     ,  )


