
"""simple docstring"""




from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
			from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

class        UpperCAmelCase_  (	a_						):
		UpperCamelCase									=c_float
		@property
		def 					_lowerCamelCase    (		self   )		->   List[Any]:
					return sizeof(self.value   )







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					,							__UpperCamelCase = 0					):
			# < 0 is possible if using a dynamic axis
			if dimension <= 0:
						__lowercase	:       int				=   fixed_dimension

			dimension -= num_token_to_add
			return dimension







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			return num_parameters * dtype.size







def       __UpperCAmelCase      (				__UpperCamelCase					):
			from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

			try:
						return AutoProcessor.from_pretrained(_lowerCAmelCase					)
			except (ValueError, OSError, KeyError):
						__lowercase	,__lowercase	:       Dict				=   None, None
						try:
									__lowercase	:       int				=   AutoTokenizer.from_pretrained(_lowerCAmelCase					)
						except (OSError, KeyError):
									pass
						try:
									__lowercase	:       Tuple				=   AutoFeatureExtractor.from_pretrained(_lowerCAmelCase					)
						except (OSError, KeyError):
									pass

						if tokenizer is not None and feature_extractor is not None:
									raise ValueError(
									    f"""Couldn't auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor."""					)
						elif tokenizer is None and feature_extractor is None:
									return None
						elif tokenizer is not None:
									return tokenizer
						else:
									return feature_extractor









"""simple docstring"""




# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue







def       __UpperCAmelCase      (				__UpperCamelCase					):
			__lowercase	:       int				=   Queue()
			__lowercase	:       str				=   [False] * len(__UpperCamelCase					)
			__lowercase	:       str				=   [-1] * len(__UpperCamelCase					)

			def bfs():
						while not queue.empty():
									__lowercase	:       int				=   queue.get()
									__lowercase	:       List[str]				=   True

									for neighbour in graph[u]:
												if neighbour == u:
															return False

												if color[neighbour] == -1:
															__lowercase	:       str				=   1 - color[u]
															queue.put(__UpperCamelCase					)

												elif color[neighbour] == color[u]:
															return False

						return True

			for i in range(len(__UpperCamelCase					)					):
						if not visited[i]:
									queue.put(__UpperCamelCase					)
									__lowercase	:       int				=   0
									if bfs() is False:
												return False

			return True


if __name__ == "__main__":
			# Adjacency List of graph
			print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))



