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

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


UpperCAmelCase_								=							logging.get_logger(__name__)


UpperCAmelCase_								=							{
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

UpperCAmelCase_								=							{
    '''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'''
        ),
    },
}

UpperCAmelCase_								=							'''</w>'''
UpperCAmelCase_								=							'''@@ '''

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						Dict:




       '''simple docstring'''






       _A=	set()
       _A=	word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)   )
              _A=	char
       return pairs


# Speech2Text2 has no max input length
UpperCAmelCase_								=							{'''facebook/s2t-wav2vec2-large-en-de''': 1_024}





class      lowerCAmelCase						(					_a			):
     _SCREAMING_SNAKE_CASE     :     str		=VOCAB_FILES_NAMES
     _SCREAMING_SNAKE_CASE     :     List[str]		=PRETRAINED_VOCAB_FILES_MAP
     _SCREAMING_SNAKE_CASE     :     str		=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _SCREAMING_SNAKE_CASE     :     List[str]		=["""input_ids""", """attention_mask"""]



     def __init__(					self				,      lowerCAmelCase__				,      lowerCAmelCase__="<s>"				,      lowerCAmelCase__="<pad>"				,      lowerCAmelCase__="</s>"				,      lowerCAmelCase__="<unk>"				,      lowerCAmelCase__=False				,      lowerCAmelCase__=None				,      **lowerCAmelCase__				,      ):
            super().__init__(
                unk_token=lowerCAmelCase__				,      bos_token=lowerCAmelCase__				,      eos_token=lowerCAmelCase__				,      pad_token=lowerCAmelCase__				,      do_lower_case=lowerCAmelCase__				,      **lowerCAmelCase__				,      )

            _A=	do_lower_case

            with open(lowerCAmelCase__				,      encoding='utf-8'       ) as vocab_handle:
                   _A=	json.load(lowerCAmelCase__       )
            _A=	{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."       )

                   _A=	None
                   _A=	None
            else:
                   with open(lowerCAmelCase__				,      encoding='utf-8'       ) as merges_handle:
                          _A=	merges_handle.read().split('\n'       )[:-1]

                   _A=	[tuple(merge.split()[:2]       ) for merge in merges]
                   _A=	dict(zip(lowerCAmelCase__				,      range(len(lowerCAmelCase__       )       )       )       )
                   _A=	{}



     @property
     def 			a__  (					self       ):
            return len(self.decoder       )



     def 			a__  (					self       ):
            return dict(self.encoder				,      **self.added_tokens_encoder       )



     def 			a__  (					self				,      lowerCAmelCase__       ):
            _A=	tuple(token[:-1]       ) + (token[-1] + BPE_TOKEN_MERGES,)
            if token in self.cache:
                   return self.cache[token]
            _A=	get_pairs(lowerCAmelCase__       )

            if not pairs:
                   return token

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

                          if word[i] == first and i < len(lowerCAmelCase__       ) - 1 and word[i + 1] == second:
                                 new_word.append(first + second       )
                                 i += 2
                          else:
                                 new_word.append(word[i]       )
                                 i += 1
                   _A=	tuple(lowerCAmelCase__       )
                   _A=	new_word
                   if len(lowerCAmelCase__       ) == 1:
                          break
                   else:
                          _A=	get_pairs(lowerCAmelCase__       )
            _A=	' '.join(lowerCAmelCase__       )
            if word == "\n  " + BPE_TOKEN_MERGES:
                   _A=	'\n' + BPE_TOKEN_MERGES

            if word.endswith(lowerCAmelCase__       ):
                   _A=	word.replace(lowerCAmelCase__				,      ''       )

            _A=	word.replace(' '				,      lowerCAmelCase__       )
            _A=	word
            return word



     def 			a__  (					self				,      lowerCAmelCase__       ):

            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:
                   _A=	text.lower()

            _A=	text.split()

            _A=	[]
            for token in text:
                   if token:
                          split_tokens.extend(list(self.bpe(lowerCAmelCase__       ).split(' '       )       )       )

            return split_tokens



     def 			a__  (					self				,      lowerCAmelCase__       ):
            return self.encoder.get(lowerCAmelCase__				,      self.encoder.get(self.unk_token       )       )



     def 			a__  (					self				,      lowerCAmelCase__       ):
            _A=	self.decoder.get(lowerCAmelCase__				,      self.unk_token       )
            return result



     def 			a__  (					self				,      lowerCAmelCase__       ):
            _A=	' '.join(lowerCAmelCase__       )

            # make sure @@ tokens are concatenated
            _A=	''.join(string.split(lowerCAmelCase__       )       )

            return string





     def 			a__  (					self				,      lowerCAmelCase__				,      lowerCAmelCase__ = None       ):
            if not os.path.isdir(lowerCAmelCase__       ):
                   logger.error(f"Vocabulary path ({save_directory}) should be a directory"       )
                   return
            _A=	os.path.join(
                lowerCAmelCase__				,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )
            _A=	os.path.join(
                lowerCAmelCase__				,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']       )

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

            _A=	0
            if self.bpe_ranks is None:
                   return (vocab_file,)

            with open(lowerCAmelCase__				,      'w'				,      encoding='utf-8'       ) as writer:
                   for bpe_tokens, token_index in sorted(self.bpe_ranks.items()				,      key=lambda lowerCAmelCase__       : 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!'       )
                                 _A=	token_index
                          writer.write(' '.join(lowerCAmelCase__       ) + '\n'       )
                          index += 1

            return (vocab_file, merges_file)
import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_								=							logging.get_logger(__name__)

UpperCAmelCase_								=							{
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}





class      lowerCAmelCase						(					_a			):
     _SCREAMING_SNAKE_CASE     :     Tuple		="""segformer"""



     def __init__(					self				,      lowerCAmelCase__=3				,      lowerCAmelCase__=4				,      lowerCAmelCase__=[2, 2, 2, 2]				,      lowerCAmelCase__=[8, 4, 2, 1]				,      lowerCAmelCase__=[32, 64, 160, 256]				,      lowerCAmelCase__=[7, 3, 3, 3]				,      lowerCAmelCase__=[4, 2, 2, 2]				,      lowerCAmelCase__=[1, 2, 5, 8]				,      lowerCAmelCase__=[4, 4, 4, 4]				,      lowerCAmelCase__="gelu"				,      lowerCAmelCase__=0.0				,      lowerCAmelCase__=0.0				,      lowerCAmelCase__=0.1				,      lowerCAmelCase__=0.02				,      lowerCAmelCase__=0.1				,      lowerCAmelCase__=1E-6				,      lowerCAmelCase__=256				,      lowerCAmelCase__=255				,      **lowerCAmelCase__				,      ):
            super().__init__(**lowerCAmelCase__       )

            if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
                   warnings.warn(
                       'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
                       ' removed, as the behaviour will default to that of reshape_last_stage = True.'				,      lowerCAmelCase__				,      )

            _A=	num_channels
            _A=	num_encoder_blocks
            _A=	depths
            _A=	sr_ratios
            _A=	hidden_sizes
            _A=	patch_sizes
            _A=	strides
            _A=	mlp_ratios
            _A=	num_attention_heads
            _A=	hidden_act
            _A=	hidden_dropout_prob
            _A=	attention_probs_dropout_prob
            _A=	classifier_dropout_prob
            _A=	initializer_range
            _A=	drop_path_rate
            _A=	layer_norm_eps
            _A=	decoder_hidden_size
            _A=	kwargs.get('reshape_last_stage'				,      lowerCAmelCase__       )
            _A=	semantic_loss_ignore_index





class      lowerCAmelCase						(					_a			):
     _SCREAMING_SNAKE_CASE     :     List[str]		=version.parse("""1.11"""			)



     @property
     def 			a__  (					self       ):
            return OrderedDict(
                [
                    ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
                ]       )



     @property
     def 			a__  (					self       ):
            return 1E-4





     @property
     def 			a__  (					self       ):
            return 12