





import copy
import random

from transformers import CLIPTokenizer


class 			lowercase				(							a_     ):



						"""simple docstring"""

						def __init__(    self			:		Union[str, Any] ,				*lowerCamelCase_			:		Dict ,				**lowerCamelCase_			:		Any					):





										'''simple docstring'''







										super().__init__(*lowerCamelCase_ ,				**lowerCamelCase_					)
										_snake_case :			List[Any]  						=   {}







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		List[Any] ,				*lowerCamelCase_			:		str ,				**lowerCamelCase_			:		Union[str, Any]					):





										'''simple docstring'''







										_snake_case :			List[str]  						=   super().add_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
										if num_added_tokens == 0:
														raise ValueError(
														    f'''The tokenizer already contains the token {placeholder_token}. Please pass a different'''
														    ' `placeholder_token` that is not already in the tokenizer.'					)







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		str ,				*lowerCamelCase_			:		List[Any] ,				lowerCamelCase_			:		Any=1 ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										_snake_case :			Dict  						=   []
										if num_vec_per_token == 1:
														self.try_adding_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
														output.append(lowerCamelCase_					)
										else:
														_snake_case :			int  						=   []
														for i in range(lowerCamelCase_					):
																		_snake_case :			List[Any]  						=   placeholder_token + f'''_{i}'''
																		self.try_adding_tokens(lowerCamelCase_ ,				*lowerCamelCase_ ,				**lowerCamelCase_					)
																		output.append(lowerCamelCase_					)
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
										for token in self.token_map:
														if token in placeholder_token:
																		raise ValueError(
																		    f'''The tokenizer already has placeholder token {token} that can get confused with'''
																		    f''' {placeholder_token}keep placeholder tokens independent'''					)
										_snake_case :			Optional[Any]  						=   output







						def 		__UpperCAmelCase       (    self			:		Dict ,				lowerCamelCase_			:		Union[str, Any] ,				lowerCamelCase_			:		List[str]=False ,				lowerCamelCase_			:		Tuple=1.0					):





										'''simple docstring'''







										if isinstance(lowerCamelCase_ ,				lowerCamelCase_					):
														_snake_case :			List[Any]  						=   []
														for i in range(len(lowerCamelCase_					)					):
																		output.append(self.replace_placeholder_tokens_in_text(text[i] ,				vector_shuffle=lowerCamelCase_					)					)
														return output
										for placeholder_token in self.token_map:
														if placeholder_token in text:
																		_snake_case :			Dict  						=   self.token_map[placeholder_token]
																		_snake_case :			Tuple  						=   tokens[: 1 + int(len(lowerCamelCase_					) * prop_tokens_to_load					)]
																		if vector_shuffle:
																						_snake_case :			Optional[int]  						=   copy.copy(lowerCamelCase_					)
																						random.shuffle(lowerCamelCase_					)
																		_snake_case :			Dict  						=   text.replace(lowerCamelCase_ ,				' '.join(lowerCamelCase_					)					)
										return text







						def __call__(    self			:		List[Any] ,				lowerCamelCase_			:		Optional[Any] ,				*lowerCamelCase_			:		Dict ,				lowerCamelCase_			:		Tuple=False ,				lowerCamelCase_			:		Union[str, Any]=1.0 ,				**lowerCamelCase_			:		Union[str, Any]					):





										'''simple docstring'''







										return super().__call__(
										    self.replace_placeholder_tokens_in_text(
										        lowerCamelCase_ ,				vector_shuffle=lowerCamelCase_ ,				prop_tokens_to_load=lowerCamelCase_					) ,				*lowerCamelCase_ ,				**lowerCamelCase_ ,				)







						def 		__UpperCAmelCase       (    self			:		str ,				lowerCamelCase_			:		int ,				*lowerCamelCase_			:		Any ,				lowerCamelCase_			:		Dict=False ,				lowerCamelCase_			:		int=1.0 ,				**lowerCamelCase_			:		Any					):





										'''simple docstring'''







										return super().encode(
										    self.replace_placeholder_tokens_in_text(
										        lowerCamelCase_ ,				vector_shuffle=lowerCamelCase_ ,				prop_tokens_to_load=lowerCamelCase_					) ,				*lowerCamelCase_ ,				**lowerCamelCase_ ,				)













import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowercase_		:				str				=						logging.get_logger(__name__)


class 			lowercase				(							a_     ):



						"""simple docstring"""

						def __init__(    self			:		int ,				*lowerCamelCase_			:		str ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										warnings.warn(
										    'The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
										    ' Please use SegformerImageProcessor instead.' ,				lowerCamelCase_ ,				)
										super().__init__(*lowerCamelCase_ ,				**lowerCamelCase_					)






