
import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowerCamelCase_						: Optional[int]         =  HUGGINGFACE_HUB_CACHE


lowerCamelCase_						: List[str]         =  """config.json"""
lowerCamelCase_						: Any         =  """diffusion_pytorch_model.bin"""
lowerCamelCase_						: Union[str, Any]         =  """diffusion_flax_model.msgpack"""
lowerCamelCase_						: Dict         =  """model.onnx"""
lowerCamelCase_						: List[Any]         =  """diffusion_pytorch_model.safetensors"""
lowerCamelCase_						: Optional[Any]         =  """weights.pb"""
lowerCamelCase_						: Optional[Any]         =  """https://huggingface.co"""
lowerCamelCase_						: Union[str, Any]         =  default_cache_path
lowerCamelCase_						: Tuple         =  """diffusers_modules"""
lowerCamelCase_						: Optional[Any]         =  os.getenv("""HF_MODULES_CACHE""", os.path.join(hf_cache_home, """modules"""))
lowerCamelCase_						: str         =  ["""fp16""", """non-ema"""]
lowerCamelCase_						: List[Any]         =  """.self_attn"""








import random







def        A__					(						lowerCamelCase     ,    lowerCamelCase     ,    lowerCamelCase = False						)  ->	dict:
				UpperCamelCase_:							dict	=						{i: [] for i in range(lowerCamelCase						)}

				# if probability is greater or equal than 1, then generate a complete graph
				if probability >= 1:
								return complete_graph(lowerCamelCase						)
				# if probability is lower or equal than 0, then return a graph without edges
				if probability <= 0:
								return graph

				# for each couple of nodes, add an edge from u to v
				# if the number randomly generated is greater than probability probability
				for i in range(lowerCamelCase						):
								for j in range(i + 1     ,    lowerCamelCase						):
												if random.random() < probability:
																graph[i].append(lowerCamelCase						)
																if not directed:
																				# if the graph is undirected, add an edge in from j to i, either
																				graph[j].append(lowerCamelCase						)
				return graph







def        A__					(						lowerCamelCase						)  ->	dict:
				return {
				    i: [j for j in range(lowerCamelCase						) if i != j] for i in range(lowerCamelCase						)
				}


if __name__ == "__main__":
							import doctest

							doctest.testmod()






