

import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a		=logging.get_logger(__name__)


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

a		={
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

a		="""</w>"""
a		="""@@ """






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


# Speech2Text2 has no max input length
a		={"""facebook/s2t-wav2vec2-large-en-de""": 1024}






class 	A_		(	lowerCamelCase__    ):
				_UpperCAmelCase   :  Any										=				VOCAB_FILES_NAMES
				_UpperCAmelCase   :  Union[str, Any]										=				PRETRAINED_VOCAB_FILES_MAP
				_UpperCAmelCase   :  Dict										=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_UpperCAmelCase   :  Tuple										=				['input_ids', 'attention_mask']
				def __init__(		self		:      Any       ,SCREAMING_SNAKE_CASE__		:      Tuple       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]="<s>"       ,SCREAMING_SNAKE_CASE__		:      List[str]="<pad>"       ,SCREAMING_SNAKE_CASE__		:      Any="</s>"       ,SCREAMING_SNAKE_CASE__		:      Optional[int]="<unk>"       ,SCREAMING_SNAKE_CASE__		:      Tuple=False       ,SCREAMING_SNAKE_CASE__		:      Dict=None       ,**SCREAMING_SNAKE_CASE__		:      str       ,):
					super().__init__(
					    unk_token=SCREAMING_SNAKE_CASE__       ,bos_token=SCREAMING_SNAKE_CASE__       ,eos_token=SCREAMING_SNAKE_CASE__       ,pad_token=SCREAMING_SNAKE_CASE__       ,do_lower_case=SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__       ,)

					__lowerCamelCase    :    str 	=			do_lower_case

					with open(SCREAMING_SNAKE_CASE__       ,encoding='utf-8') as vocab_handle:
						__lowerCamelCase    :    Any 	=			json.load(SCREAMING_SNAKE_CASE__)
					__lowerCamelCase    :    Optional[int] 	=			{v: k for k, v in self.encoder.items()}

					if merges_file is None:
						logger.info(F"No merges files provided. {self.__class__.__name__} can only be used for decoding.")

						__lowerCamelCase    :    Optional[int] 	=			None
						__lowerCamelCase    :    Any 	=			None
					else:
						with open(SCREAMING_SNAKE_CASE__       ,encoding='utf-8') as merges_handle:
							__lowerCamelCase    :    Any 	=			merges_handle.read().split('\n')[:-1]

						__lowerCamelCase    :    str 	=			[tuple(merge.split()[:2]) for merge in merges]
						__lowerCamelCase    :    Union[str, Any] 	=			dict(zip(SCREAMING_SNAKE_CASE__       ,range(len(SCREAMING_SNAKE_CASE__))))
						__lowerCamelCase    :    Union[str, Any] 	=			{}
				@property
				def    lowerCAmelCase					(		self		:      Optional[Any]):
					return len(self.decoder)
				def    lowerCAmelCase					(		self		:      Optional[int]):
					return dict(self.encoder       ,**self.added_tokens_encoder)
				def    lowerCAmelCase					(		self		:      str       ,SCREAMING_SNAKE_CASE__		:      List[Any]):
					__lowerCamelCase    :    Optional[Any] 	=			tuple(token[:-1]) + (token[-1] + BPE_TOKEN_MERGES,)
					if token in self.cache:
						return self.cache[token]
					__lowerCamelCase    :    List[str] 	=			get_pairs(SCREAMING_SNAKE_CASE__)

					if not pairs:
						return token

					while True:
						__lowerCamelCase    :    Optional[Any] 	=			min(SCREAMING_SNAKE_CASE__       ,key=lambda SCREAMING_SNAKE_CASE__: self.bpe_ranks.get(SCREAMING_SNAKE_CASE__       ,float('inf')))
						if bigram not in self.bpe_ranks:
							break
						__lowerCamelCase	,			__lowerCamelCase    :    Dict 	=			bigram
						__lowerCamelCase    :    List[str] 	=			[]
						__lowerCamelCase    :    str 	=			0
						while i < len(SCREAMING_SNAKE_CASE__):
							try:
								__lowerCamelCase    :    Dict 	=			word.index(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							except ValueError:
								new_word.extend(word[i:])
								break
							else:
								new_word.extend(word[i:j])
								__lowerCamelCase    :    Any 	=			j

							if word[i] == first and i < len(SCREAMING_SNAKE_CASE__) - 1 and word[i + 1] == second:
								new_word.append(first + second)
								i += 2
							else:
								new_word.append(word[i])
								i += 1
						__lowerCamelCase    :    Any 	=			tuple(SCREAMING_SNAKE_CASE__)
						__lowerCamelCase    :    str 	=			new_word
						if len(SCREAMING_SNAKE_CASE__) == 1:
							break
						else:
							__lowerCamelCase    :    List[Any] 	=			get_pairs(SCREAMING_SNAKE_CASE__)
					__lowerCamelCase    :    Union[str, Any] 	=			' '.join(SCREAMING_SNAKE_CASE__)
					if word == "\n  " + BPE_TOKEN_MERGES:
						__lowerCamelCase    :    Optional[int] 	=			'\n' + BPE_TOKEN_MERGES

					if word.endswith(SCREAMING_SNAKE_CASE__):
						__lowerCamelCase    :    int 	=			word.replace(SCREAMING_SNAKE_CASE__       ,'')

					__lowerCamelCase    :    Optional[Any] 	=			word.replace(' '       ,SCREAMING_SNAKE_CASE__)
					__lowerCamelCase    :    List[Any] 	=			word
					return word
				def    lowerCAmelCase					(		self		:      Dict       ,SCREAMING_SNAKE_CASE__		:      int):







					if self.bpe_ranks is None:
						raise ValueError(
						    'This tokenizer was instantiated without a `merges.txt` file, so'
						    ' that it can only be used for decoding, not for encoding.'
						    'Make sure to provide `merges.txt` file at instantiation to enable '
						    'encoding.')

					if self.do_lower_case:
						__lowerCamelCase    :    Tuple 	=			text.lower()

					__lowerCamelCase    :    str 	=			text.split()

					__lowerCamelCase    :    Any 	=			[]
					for token in text:
						if token:
							split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE__).split(' ')))

					return split_tokens
				def    lowerCAmelCase					(		self		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      List[Any]):
					return self.encoder.get(SCREAMING_SNAKE_CASE__       ,self.encoder.get(self.unk_token))
				def    lowerCAmelCase					(		self		:      Optional[Any]       ,SCREAMING_SNAKE_CASE__		:      Any):
					__lowerCamelCase    :    str 	=			self.decoder.get(SCREAMING_SNAKE_CASE__       ,self.unk_token)
					return result
				def    lowerCAmelCase					(		self		:      Optional[int]       ,SCREAMING_SNAKE_CASE__		:      Any):
					__lowerCamelCase    :    Tuple 	=			' '.join(SCREAMING_SNAKE_CASE__)

					# make sure @@ tokens are concatenated
					__lowerCamelCase    :    Dict 	=			''.join(string.split(SCREAMING_SNAKE_CASE__))

					return string


				def    lowerCAmelCase					(		self		:      List[str]       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]       ,SCREAMING_SNAKE_CASE__		:      List[Any] = None):







					if not os.path.isdir(SCREAMING_SNAKE_CASE__):
						logger.error(F"Vocabulary path ({save_directory}) should be a directory")
						return
					__lowerCamelCase    :    Any 	=			os.path.join(
					    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
					__lowerCamelCase    :    List[str] 	=			os.path.join(
					    SCREAMING_SNAKE_CASE__       ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'])

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

					__lowerCamelCase    :    List[Any] 	=			0
					if self.bpe_ranks is None:
						return (vocab_file,)

					with open(SCREAMING_SNAKE_CASE__       ,'w'       ,encoding='utf-8') as writer:
						for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,key=lambda SCREAMING_SNAKE_CASE__: kv[1]):
							if index != token_index:
								logger.warning(
								    F"Saving vocabulary to {merges_file}: BPE merge indices are not consecutive."
								    ' Please check that the tokenizer is not corrupted!')
								__lowerCamelCase    :    Optional[Any] 	=			token_index
							writer.write(' '.join(SCREAMING_SNAKE_CASE__) + '\n')
							index += 1

					return (vocab_file, merges_file)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a		={
    """configuration_mask2former""": [
        """MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Mask2FormerConfig""",
    ],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a		=["""Mask2FormerImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a		=[
					    """MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """Mask2FormerForUniversalSegmentation""",
					    """Mask2FormerModel""",
					    """Mask2FormerPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_maskaformer import MaskaFormerImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskaformer import (
										    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskaFormerForUniversalSegmentation,
										    MaskaFormerModel,
										    MaskaFormerPreTrainedModel,
										)


else:
					import sys

					a		=_LazyModule(__name__, globals()["""__file__"""], _import_structure)




