






'''simple docstring'''







from collections.abc import Sequence
from queue import Queue
class 			_lowercase						:







     def __init__( self    ,   A__    ,   A__    ,   A__    ,   A__=None    ,   A__=None    ) ->	List[str]:
      snake_case				=			start
      snake_case				=			end
      snake_case				=			val
      snake_case				=			(start + end) // 2
      snake_case				=			left
      snake_case				=			right







     def __repr__( self    ) ->	List[str]:
      return F"""SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})"""




class 			_lowercase						:







     def __init__( self    ,   A__    ,   A__    ) ->	Optional[int]:
      snake_case				=			collection
      snake_case				=			function
      if self.collection:
       snake_case				=			self._build_tree(0    ,   len(A__    ) - 1    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	Optional[Any]:
      self._update_tree(self.root    ,   A__    ,   A__    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	Any:
      return self._query_range(self.root    ,   A__    ,   A__    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	Optional[int]:

      if start == end:
       return SegmentTreeNode(A__    ,   A__    ,   self.collection[start]    )
      snake_case				=			(start + end) // 2
      snake_case				=			self._build_tree(A__    ,   A__    )
      snake_case				=			self._build_tree(mid + 1    ,   A__    )
      return SegmentTreeNode(A__    ,   A__    ,   self.fn(left.val    ,   right.val    )    ,   A__    ,   A__    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ) ->	Tuple:

      if node.start == i and node.end == i:
       snake_case				=			val
       return
      if i <= node.mid:
       self._update_tree(node.left    ,   A__    ,   A__    )
      else:
       self._update_tree(node.right    ,   A__    ,   A__    )
      snake_case				=			self.fn(node.left.val    ,   node.right.val    )







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ) ->	List[Any]:

      if node.start == i and node.end == j:
       return node.val

      if i <= node.mid:
       if j <= node.mid:
        # range in left child tree
        return self._query_range(node.left    ,   A__    ,   A__    )
       else:
        # range in left child tree and right child tree
        return self.fn(
            self._query_range(node.left    ,   A__    ,   node.mid    )    ,   self._query_range(node.right    ,   node.mid + 1    ,   A__    )    ,   )
      else:
       # range in right child tree
       return self._query_range(node.right    ,   A__    ,   A__    )







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

      if self.root is not None:
       snake_case				=			Queue()
       queue.put(self.root    )
       while not queue.empty():
        snake_case				=			queue.get()
        yield node

        if node.left is not None:
         queue.put(node.left    )

        if node.right is not None:
         queue.put(node.right    )


if __name__ == "__main__":
   import operator

   for fn in [operator.add, max, min]:
      print('*' * 50)
      _lowercase       						=			SegmentTree([2, 1, 5, 3, 4], fn)
      for node in arr.traverse():
         print(node)
      print()

      arr.update(1, 5)
      for node in arr.traverse():
         print(node)
      print()

      print(arr.query_range(3, 4))  # 7
      print(arr.query_range(2, 2))  # 5
      print(arr.query_range(1, 3))  # 13
      print()








'''simple docstring'''







import warnings

from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum

from ...processing_utils import ProcessorMixin


if is_torch_available():
   import torch
class 			_lowercase						(       __a					):
     _UpperCAmelCase										=					'''char'''
     _UpperCAmelCase										=					'''bpe'''
     _UpperCAmelCase										=					'''wp'''




_lowercase       						=			(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)
class 			_lowercase						(       __a					):
     _UpperCAmelCase										=					['''image_processor''', '''char_tokenizer''']
     _UpperCAmelCase										=					'''ViTImageProcessor'''
     _UpperCAmelCase										=					'''MgpstrTokenizer'''







     def __init__( self    ,   A__=None    ,   A__=None    ,   **A__    ) ->	List[Any]:
      snake_case				=			None
      if "feature_extractor" in kwargs:
       warnings.warn(
           '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
           ''' instead.'''    ,   A__    ,   )
       snake_case				=			kwargs.pop('''feature_extractor'''    )

      snake_case				=			image_processor if image_processor is not None else feature_extractor
      if image_processor is None:
       raise ValueError('''You need to specify an `image_processor`.'''    )
      if tokenizer is None:
       raise ValueError('''You need to specify a `tokenizer`.'''    )

      snake_case				=			tokenizer
      snake_case				=			AutoTokenizer.from_pretrained('''gpt2'''    )
      snake_case				=			AutoTokenizer.from_pretrained('''bert-base-uncased'''    )

      super().__init__(A__    ,   A__    )







     def __call__( self    ,   A__=None    ,   A__=None    ,   A__=None    ,   **A__    ) ->	List[str]:
      if images is None and text is None:
       raise ValueError('''You need to specify either an `images` or `text` input to process.'''    )

      if images is not None:
       snake_case				=			self.image_processor(A__    ,   return_tensors=A__    ,   **A__    )
      if text is not None:
       snake_case				=			self.char_tokenizer(A__    ,   return_tensors=A__    ,   **A__    )

      if text is None:
       return inputs
      elif images is None:
       return encodings
      else:
       snake_case				=			encodings['''input_ids''']
       return inputs







     def     UpperCamelCase			( self    ,   A__    ) ->	Dict:
      snake_case				,		snake_case				,		snake_case				=			sequences
      snake_case				=			char_preds.size(0    )

      snake_case				,		snake_case				=			self._decode_helper(A__    ,   '''char'''    )
      snake_case				,		snake_case				=			self._decode_helper(A__    ,   '''bpe'''    )
      snake_case				,		snake_case				=			self._decode_helper(A__    ,   '''wp'''    )

      snake_case				=			[]
      snake_case				=			[]
      for i in range(A__    ):
       snake_case				=			[char_scores[i], bpe_scores[i], wp_scores[i]]
       snake_case				=			[char_strs[i], bpe_strs[i], wp_strs[i]]
       snake_case				=			scores.index(max(A__    )    )
       final_strs.append(strs[max_score_index]    )
       final_scores.append(scores[max_score_index]    )

      snake_case				=			{}
      snake_case				=			final_strs
      snake_case				=			final_scores
      snake_case				=			char_strs
      snake_case				=			bpe_strs
      snake_case				=			wp_strs
      return out







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	Optional[Any]:
      if format == DecodeType.CHARACTER:
       snake_case				=			self.char_decode
       snake_case				=			1
       snake_case				=			'''[s]'''
      elif format == DecodeType.BPE:
       snake_case				=			self.bpe_decode
       snake_case				=			2
       snake_case				=			'''#'''
      elif format == DecodeType.WORDPIECE:
       snake_case				=			self.wp_decode
       snake_case				=			1_02
       snake_case				=			'''[SEP]'''
      else:
       raise ValueError(F"""Format {format} is not supported."""    )

      snake_case				,		snake_case				=			[], []
      snake_case				=			pred_logits.size(0    )
      snake_case				=			pred_logits.size(1    )
      snake_case				,		snake_case				=			pred_logits.topk(1    ,   dim=-1    ,   largest=A__    ,   sorted=A__    )
      snake_case				=			preds_index.view(-1    ,   A__    )[:, 1:]
      snake_case				=			decoder(A__    )
      snake_case				,		snake_case				=			torch.nn.functional.softmax(A__    ,   dim=2    ).max(dim=2    )
      snake_case				=			preds_max_prob[:, 1:]

      for index in range(A__    ):
       snake_case				=			preds_str[index].find(A__    )
       snake_case				=			preds_str[index][:pred_eos]
       snake_case				=			preds_index[index].cpu().tolist()
       snake_case				=			pred_index.index(A__    ) if eos_token in pred_index else -1
       snake_case				=			preds_max_prob[index][: pred_eos_index + 1]
       snake_case				=			pred_max_prob.cumprod(dim=0    )[-1] if pred_max_prob.nelement() != 0 else 0.0
       dec_strs.append(A__    )
       conf_scores.append(A__    )

      return dec_strs, conf_scores







     def     UpperCamelCase			( self    ,   A__    ) ->	int:
      snake_case				=			[seq.replace(''' '''    ,   ''''''    ) for seq in self.char_tokenizer.batch_decode(A__    )]
      return decode_strs







     def     UpperCamelCase			( self    ,   A__    ) ->	List[str]:
      return self.bpe_tokenizer.batch_decode(A__    )







     def     UpperCamelCase			( self    ,   A__    ) ->	Union[str, Any]:
      snake_case				=			[seq.replace(''' '''    ,   ''''''    ) for seq in self.wp_tokenizer.batch_decode(A__    )]
      return decode_strs

