
"""simple docstring"""





# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

__magic_name__       =			TypeVar("T")
class 						SCREAMING_SNAKE_CASE_ (						Generic[T] ):




		"""simple docstring"""





		def __init__(     self							,  lowerCAmelCase__ = True):
				__SCREAMING_SNAKE_CASE            = {}  # dictionary of lists
				__SCREAMING_SNAKE_CASE            = directed




		def 	snake_case_     (     self							,  lowerCAmelCase__							,  lowerCAmelCase__):

				if not self.directed:  # For undirected graphs
						# if both source vertex and destination vertex are both present in the
						# adjacency list, add destination vertex to source vertex list of adjacent
						# vertices and add source vertex to destination vertex list of adjacent
						# vertices.
						if source_vertex in self.adj_list and destination_vertex in self.adj_list:
								self.adj_list[source_vertex].append(lowerCAmelCase__)
								self.adj_list[destination_vertex].append(lowerCAmelCase__)
						# if only source vertex is present in adjacency list, add destination vertex
						# to source vertex list of adjacent vertices, then create a new vertex with
						# destination vertex as key and assign a list containing the source vertex
						# as it's first adjacent vertex.
						elif source_vertex in self.adj_list:
								self.adj_list[source_vertex].append(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = [source_vertex]
						# if only destination vertex is present in adjacency list, add source vertex
						# to destination vertex list of adjacent vertices, then create a new vertex
						# with source vertex as key and assign a list containing the source vertex
						# as it's first adjacent vertex.
						elif destination_vertex in self.adj_list:
								self.adj_list[destination_vertex].append(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = [destination_vertex]
						# if both source vertex and destination vertex are not present in adjacency
						# list, create a new vertex with source vertex as key and assign a list
						# containing the destination vertex as it's first adjacent vertex also
						# create a new vertex with destination vertex as key and assign a list
						# containing the source vertex as it's first adjacent vertex.
						else:
								__SCREAMING_SNAKE_CASE            = [destination_vertex]
								__SCREAMING_SNAKE_CASE            = [source_vertex]
				else:  # For directed graphs
						# if both source vertex and destination vertex are present in adjacency
						# list, add destination vertex to source vertex list of adjacent vertices.
						if source_vertex in self.adj_list and destination_vertex in self.adj_list:
								self.adj_list[source_vertex].append(lowerCAmelCase__)
						# if only source vertex is present in adjacency list, add destination
						# vertex to source vertex list of adjacent vertices and create a new vertex
						# with destination vertex as key, which has no adjacent vertex
						elif source_vertex in self.adj_list:
								self.adj_list[source_vertex].append(lowerCAmelCase__)
								__SCREAMING_SNAKE_CASE            = []
						# if only destination vertex is present in adjacency list, create a new
						# vertex with source vertex as key and assign a list containing destination
						# vertex as first adjacent vertex
						elif destination_vertex in self.adj_list:
								__SCREAMING_SNAKE_CASE            = [destination_vertex]
						# if both source vertex and destination vertex are not present in adjacency
						# list, create a new vertex with source vertex as key and a list containing
						# destination vertex as it's first adjacent vertex. Then create a new vertex
						# with destination vertex as key, which has no adjacent vertex
						else:
								__SCREAMING_SNAKE_CASE            = [destination_vertex]
								__SCREAMING_SNAKE_CASE            = []

				return self




		def __repr__(     self):
				return pformat(self.adj_list)






"""simple docstring"""





from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class 						SCREAMING_SNAKE_CASE_ (						__a ):




		"""simple docstring"""





		__lowercase							:  List[Any]						   =		['''image_processor''', '''tokenizer''']
		__lowercase							:  List[Any]						   =		'''BridgeTowerImageProcessor'''
		__lowercase							:  Tuple						   =		('''RobertaTokenizer''', '''RobertaTokenizerFast''')




		def __init__(     self							,  lowerCAmelCase__							,  lowerCAmelCase__):
				super().__init__(lowerCAmelCase__							,  lowerCAmelCase__)




		def __call__(     self							,  lowerCAmelCase__							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = True							,  lowerCAmelCase__ = False							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = 0							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = None							,  lowerCAmelCase__ = False							,  lowerCAmelCase__ = False							,  lowerCAmelCase__ = False							,  lowerCAmelCase__ = False							,  lowerCAmelCase__ = True							,  lowerCAmelCase__ = None							,  **lowerCAmelCase__							,  ):
				__SCREAMING_SNAKE_CASE            = self.tokenizer(
				    text=lowerCAmelCase__							,  add_special_tokens=lowerCAmelCase__							,  padding=lowerCAmelCase__							,  truncation=lowerCAmelCase__							,  max_length=lowerCAmelCase__							,  stride=lowerCAmelCase__							,  pad_to_multiple_of=lowerCAmelCase__							,  return_token_type_ids=lowerCAmelCase__							,  return_attention_mask=lowerCAmelCase__							,  return_overflowing_tokens=lowerCAmelCase__							,  return_special_tokens_mask=lowerCAmelCase__							,  return_offsets_mapping=lowerCAmelCase__							,  return_length=lowerCAmelCase__							,  verbose=lowerCAmelCase__							,  return_tensors=lowerCAmelCase__							,  **lowerCAmelCase__							,  )
				# add pixel_values + pixel_mask
				__SCREAMING_SNAKE_CASE            = self.image_processor(
				    lowerCAmelCase__							,  return_tensors=lowerCAmelCase__							,  do_normalize=lowerCAmelCase__							,  do_center_crop=lowerCAmelCase__							,  **lowerCAmelCase__)
				encoding.update(lowerCAmelCase__)

				return encoding




		def 	snake_case_     (     self							,  *lowerCAmelCase__							,  **lowerCAmelCase__):
				return self.tokenizer.batch_decode(*lowerCAmelCase__							,  **lowerCAmelCase__)




		def 	snake_case_     (     self							,  *lowerCAmelCase__							,  **lowerCAmelCase__):
				return self.tokenizer.decode(*lowerCAmelCase__							,  **lowerCAmelCase__)




		@property
		def 	snake_case_     (     self):
				__SCREAMING_SNAKE_CASE            = self.tokenizer.model_input_names
				__SCREAMING_SNAKE_CASE            = self.image_processor.model_input_names
				return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))




