




import re
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			snake_case_   		=       ['''image_processor''', '''tokenizer''']
			snake_case_   		=       '''AutoImageProcessor'''
			snake_case_   		=       '''AutoTokenizer'''


			def __init__(      self			,						lowerCamelCase__=None			,						lowerCamelCase__=None			,						**lowerCamelCase__							)    ->      Union[str, Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    None
							if "feature_extractor" in kwargs:
											warnings.warn(
											    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
											    ' instead.'			,						lowerCamelCase__			,						)
											__lowerCamelCase		       =    kwargs.pop('feature_extractor'							)

							__lowerCamelCase		       =    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`.'							)

							super().__init__(lowerCamelCase__			,						lowerCamelCase__							)
							__lowerCamelCase		       =    self.image_processor
							__lowerCamelCase		       =    False


			def __call__(      self			,						*lowerCamelCase__			,						**lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							# For backward compatibility
							if self._in_target_context_manager:
											return self.current_processor(*lowerCamelCase__			,						**lowerCamelCase__							)

							__lowerCamelCase		       =    kwargs.pop('images'			,						lowerCamelCase__							)
							__lowerCamelCase		       =    kwargs.pop('text'			,						lowerCamelCase__							)
							if len(lowerCamelCase__							) > 0:
											__lowerCamelCase		       =    args[0]
											__lowerCamelCase		       =    args[1:]

							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:
											__lowerCamelCase		       =    self.image_processor(lowerCamelCase__			,						*lowerCamelCase__			,						**lowerCamelCase__							)
							if text is not None:
											__lowerCamelCase		       =    self.tokenizer(lowerCamelCase__			,						**lowerCamelCase__							)

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


			def       lowercase_    (      self			,						*lowerCamelCase__			,						**lowerCamelCase__							)    ->      List[Any]:



							'''simple docstring'''
							return self.tokenizer.batch_decode(*lowerCamelCase__			,						**lowerCamelCase__							)


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



							'''simple docstring'''
							return self.tokenizer.decode(*lowerCamelCase__			,						**lowerCamelCase__							)


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



							'''simple docstring'''
							warnings.warn(
							    '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
							    'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
							    'your images inputs, or in a separate call.'							)
							__lowerCamelCase		       =    True
							__lowerCamelCase		       =    self.tokenizer
							yield
							__lowerCamelCase		       =    self.image_processor
							__lowerCamelCase		       =    False


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__=False			,						lowerCamelCase__=None							)    ->      Dict:



							'''simple docstring'''
							if added_vocab is None:
											__lowerCamelCase		       =    self.tokenizer.get_added_vocab()

							__lowerCamelCase		       =    {}

							while tokens:
											__lowerCamelCase		       =    re.search(R'<s_(.*?)>'			,						lowerCamelCase__			,						re.IGNORECASE							)
											if start_token is None:
															break
											__lowerCamelCase		       =    start_token.group(1							)
											__lowerCamelCase		       =    re.search(Rf"""</s_{key}>"""			,						lowerCamelCase__			,						re.IGNORECASE							)
											__lowerCamelCase		       =    start_token.group()
											if end_token is None:
															__lowerCamelCase		       =    tokens.replace(lowerCamelCase__			,						''							)
											else:
															__lowerCamelCase		       =    end_token.group()
															__lowerCamelCase		       =    re.escape(lowerCamelCase__							)
															__lowerCamelCase		       =    re.escape(lowerCamelCase__							)
															__lowerCamelCase		       =    re.search(f"""{start_token_escaped}(.*?){end_token_escaped}"""			,						lowerCamelCase__			,						re.IGNORECASE							)
															if content is not None:
																			__lowerCamelCase		       =    content.group(1							).strip()
																			if r"<s_" in content and r"</s_" in content:  # non-leaf node
																							__lowerCamelCase		       =    self.tokenajson(lowerCamelCase__			,						is_inner_value=lowerCamelCase__			,						added_vocab=lowerCamelCase__							)
																							if value:
																											if len(lowerCamelCase__							) == 1:
																															__lowerCamelCase		       =    value[0]
																											__lowerCamelCase		       =    value
																			else:  # leaf nodes
																							__lowerCamelCase		       =    []
																							for leaf in content.split(R'<sep/>'							):
																											__lowerCamelCase		       =    leaf.strip()
																											if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
																															__lowerCamelCase		       =    leaf[1:-2]  # for categorical special tokens
																											output[key].append(lowerCamelCase__							)
																							if len(output[key]							) == 1:
																											__lowerCamelCase		       =    output[key][0]

															__lowerCamelCase		       =    tokens[tokens.find(lowerCamelCase__							) + len(lowerCamelCase__							) :].strip()
															if tokens[:6] == r"<sep/>":  # non-leaf nodes
																			return [output] + self.tokenajson(tokens[6:]			,						is_inner_value=lowerCamelCase__			,						added_vocab=lowerCamelCase__							)

							if len(lowerCamelCase__							):
											return [output] if is_inner_value else output
							else:
											return [] if is_inner_value else {"text_sequence": tokens}


			@property
			def       lowercase_    (      self							)    ->      Dict:



							'''simple docstring'''
							warnings.warn(
							    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'			,						lowerCamelCase__			,						)
							return self.image_processor_class






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



							'''simple docstring'''
							warnings.warn(
							    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'			,						lowerCamelCase__			,						)
							return self.image_processor








class     __lowerCAmelCase :

			"""simple docstring"""







			def __init__(      self							)    ->      Any:



							'''simple docstring'''
							__lowerCamelCase		       =    0
							__lowerCamelCase		       =    0
							__lowerCamelCase		       =    {}


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Tuple:



							'''simple docstring'''
							if vertex not in self.adjacency:
											__lowerCamelCase		       =    {}
											self.num_vertices += 1


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							self.add_vertex(lowerCamelCase__							)
							self.add_vertex(lowerCamelCase__							)

							if head == tail:
											return

							__lowerCamelCase		       =    weight
							__lowerCamelCase		       =    weight


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



							'''simple docstring'''
							__lowerCamelCase		       =    self.get_edges()
							for edge in edges:
											__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase		       =    edge
											edges.remove((tail, head, weight)							)
							for i in range(len(lowerCamelCase__							)							):
											__lowerCamelCase		       =    list(edges[i]							)

							edges.sort(key=lambda lowerCamelCase__							: e[2]							)
							for i in range(len(lowerCamelCase__							) - 1							):
											if edges[i][2] >= edges[i + 1][2]:
															__lowerCamelCase		       =    edges[i][2] + 1
							for edge in edges:
											__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase		       =    edge
											__lowerCamelCase		       =    weight
											__lowerCamelCase		       =    weight


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



							'''simple docstring'''
							__lowerCamelCase		       =    ''
							for tail in self.adjacency:
											for head in self.adjacency[tail]:
															__lowerCamelCase		       =    self.adjacency[head][tail]
															string += f"""{head} -> {tail} == {weight}\n"""
							return string.rstrip('\n'							)


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



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for tail in self.adjacency:
											for head in self.adjacency[tail]:
															output.append((tail, head, self.adjacency[head][tail])							)
							return output


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



							'''simple docstring'''
							return self.adjacency.keys()


			@staticmethod
			def       lowercase_    (      lowerCamelCase__=None			,						lowerCamelCase__=None							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    Graph()
							if vertices is None:
											__lowerCamelCase		       =    []
							if edges is None:
											__lowerCamelCase		       =    []
							for vertex in vertices:
											g.add_vertex(lowerCamelCase__							)
							for edge in edges:
											g.add_edge(*lowerCamelCase__							)
							return g







			class     __lowerCAmelCase :

						"""simple docstring"""







						def __init__(      self							)    ->      Tuple:



										'''simple docstring'''
										__lowerCamelCase		       =    {}
										__lowerCamelCase		       =    {}


						def __len__(      self							)    ->      Tuple:



										'''simple docstring'''
										return len(self.parent							)


						def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[Any]:



										'''simple docstring'''
										if item in self.parent:
														return self.find(lowerCamelCase__							)

										__lowerCamelCase		       =    item
										__lowerCamelCase		       =    0
										return item


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



										'''simple docstring'''
										if item not in self.parent:
														return self.make_set(lowerCamelCase__							)
										if item != self.parent[item]:
														__lowerCamelCase		       =    self.find(self.parent[item]							)
										return self.parent[item]






						def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__							)    ->      int:



										'''simple docstring'''
										__lowerCamelCase		       =    self.find(lowerCamelCase__							)
										__lowerCamelCase		       =    self.find(lowerCamelCase__							)

										if roota == roota:
														return roota

										if self.rank[roota] > self.rank[roota]:
														__lowerCamelCase		       =    roota
														return roota

										if self.rank[roota] < self.rank[roota]:
														__lowerCamelCase		       =    roota
														return roota

										if self.rank[roota] == self.rank[roota]:
														self.rank[roota] += 1
														__lowerCamelCase		       =    roota
														return roota
										return None




			@staticmethod
			def       lowercase_    (      lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    graph.num_vertices

							__lowerCamelCase		       =    Graph.UnionFind()
							__lowerCamelCase		       =    []
							while num_components > 1:
											__lowerCamelCase		       =    {}
											for vertex in graph.get_vertices():
															__lowerCamelCase		       =    -1

											__lowerCamelCase		       =    graph.get_edges()
											for edge in edges:
															__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase		       =    edge
															edges.remove((tail, head, weight)							)
											for edge in edges:
															__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase		       =    edge
															__lowerCamelCase		       =    union_find.find(lowerCamelCase__							)
															__lowerCamelCase		       =    union_find.find(lowerCamelCase__							)
															if seta != seta:
																			if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																							__lowerCamelCase		       =    [head, tail, weight]

																			if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																							__lowerCamelCase		       =    [head, tail, weight]
											for vertex in cheap_edge:
															if cheap_edge[vertex] != -1:
																			__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase		       =    cheap_edge[vertex]
																			if union_find.find(lowerCamelCase__							) != union_find.find(lowerCamelCase__							):
																							union_find.union(lowerCamelCase__			,						lowerCamelCase__							)
																							mst_edges.append(cheap_edge[vertex]							)
																							__lowerCamelCase		       =    num_components - 1
							__lowerCamelCase		       =    Graph.build(edges=lowerCamelCase__							)
							return mst


