



import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__A				    =						logging.get_logger(__name__)

__A				    =						{
    '''facebook/musicgen-small''': '''https://huggingface.co/facebook/musicgen-small/resolve/main/config.json''',
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}






class 		lowercase						( snake_case__):






	"""simple docstring"""


	a__      :					List[Any]		   =							"musicgen_decoder"
	a__      :					str		   =							["past_key_values"]




	def __init__(	self	:						Optional[Any]						,  __UpperCAmelCase	:						Tuple=2_048						,  __UpperCAmelCase	:						str=2_048						,  __UpperCAmelCase	:						List[str]=24						,  __UpperCAmelCase	:						List[str]=4_096						,  __UpperCAmelCase	:						List[Any]=16						,  __UpperCAmelCase	:						Union[str, Any]=0.0						,  __UpperCAmelCase	:						Union[str, Any]=True						,  __UpperCAmelCase	:						int="gelu"						,  __UpperCAmelCase	:						List[Any]=1_024						,  __UpperCAmelCase	:						str=0.1						,  __UpperCAmelCase	:						str=0.0						,  __UpperCAmelCase	:						str=0.0						,  __UpperCAmelCase	:						Union[str, Any]=0.02						,  __UpperCAmelCase	:						int=False						,  __UpperCAmelCase	:						Optional[int]=4						,  __UpperCAmelCase	:						Optional[Any]=2_048						,  __UpperCAmelCase	:						Dict=2_048						,  __UpperCAmelCase	:						List[str]=None						,  __UpperCAmelCase	:						Dict=False						,  **__UpperCAmelCase	:						int						,  )			-> int:
							UpperCAmelCase_=   vocab_size
							UpperCAmelCase_=   max_position_embeddings
							UpperCAmelCase_=   hidden_size
							UpperCAmelCase_=   ffn_dim
							UpperCAmelCase_=   num_hidden_layers
							UpperCAmelCase_=   num_attention_heads
							UpperCAmelCase_=   dropout
							UpperCAmelCase_=   attention_dropout
							UpperCAmelCase_=   activation_dropout
							UpperCAmelCase_=   activation_function
							UpperCAmelCase_=   initializer_factor
							UpperCAmelCase_=   layerdrop
							UpperCAmelCase_=   use_cache
							UpperCAmelCase_=   scale_embedding  # scale factor will be sqrt(d_model) if True
							UpperCAmelCase_=   num_codebooks
							super().__init__(
							    pad_token_id=__UpperCAmelCase						,  bos_token_id=__UpperCAmelCase						,  eos_token_id=__UpperCAmelCase						,  tie_word_embeddings=__UpperCAmelCase						,  **__UpperCAmelCase						,  )






class 		lowercase						( snake_case__):






	"""simple docstring"""


	a__      :					List[Any]		   =							"musicgen"
	a__      :					Tuple		   =							True




	def __init__(	self	:						Tuple						,  **__UpperCAmelCase	:						List[Any]     )			-> int:
							super().__init__(**__UpperCAmelCase     )
							if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
													raise ValueError("""Config has to be initialized with text_encoder, audio_encoder and decoder config"""     )

							UpperCAmelCase_=   kwargs.pop("""text_encoder"""     )
							UpperCAmelCase_=   text_encoder_config.pop("""model_type"""     )

							UpperCAmelCase_=   kwargs.pop("""audio_encoder"""     )
							UpperCAmelCase_=   audio_encoder_config.pop("""model_type"""     )

							UpperCAmelCase_=   kwargs.pop("""decoder"""     )

							UpperCAmelCase_=   AutoConfig.for_model(__UpperCAmelCase						,  **__UpperCAmelCase     )
							UpperCAmelCase_=   AutoConfig.for_model(__UpperCAmelCase						,  **__UpperCAmelCase     )
							UpperCAmelCase_=   MusicgenDecoderConfig(**__UpperCAmelCase     )
							UpperCAmelCase_=   True




	@classmethod
	def   _SCREAMING_SNAKE_CASE		(	cls	:						Any						,  __UpperCAmelCase	:						PretrainedConfig						,  __UpperCAmelCase	:						PretrainedConfig						,  __UpperCAmelCase	:						MusicgenDecoderConfig						,  **__UpperCAmelCase	:						int						,  )			-> Union[str, Any]:
							return cls(
							    text_encoder=text_encoder_config.to_dict()						,  audio_encoder=audio_encoder_config.to_dict()						,  decoder=decoder_config.to_dict()						,  **__UpperCAmelCase						,  )




	def   _SCREAMING_SNAKE_CASE		(	self	:						Dict     )			-> Optional[int]:
							UpperCAmelCase_=   copy.deepcopy(self.__dict__     )
							UpperCAmelCase_=   self.text_encoder.to_dict()
							UpperCAmelCase_=   self.audio_encoder.to_dict()
							UpperCAmelCase_=   self.decoder.to_dict()
							UpperCAmelCase_=   self.__class__.model_type
							return output









from __future__ import annotations

import random

# Adjacency list representation of this graph:
# https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
__A				    =						{
    '''1''': ['''2''', '''3''', '''4''', '''5'''],
    '''2''': ['''1''', '''3''', '''4''', '''5'''],
    '''3''': ['''1''', '''2''', '''4''', '''5''', '''10'''],
    '''4''': ['''1''', '''2''', '''3''', '''5''', '''6'''],
    '''5''': ['''1''', '''2''', '''3''', '''4''', '''7'''],
    '''6''': ['''7''', '''8''', '''9''', '''10''', '''4'''],
    '''7''': ['''6''', '''8''', '''9''', '''10''', '''5'''],
    '''8''': ['''6''', '''7''', '''9''', '''10'''],
    '''9''': ['''6''', '''7''', '''8''', '''10'''],
    '''10''': ['''6''', '''7''', '''8''', '''9''', '''3'''],
}



def        __a     (    lowerCAmelCase_   :					dict[str, list[str]]				)      -> set[tuple[str, str]]:






						'''simple docstring'''



						UpperCAmelCase_=   {node: {node} for node in graph}

						UpperCAmelCase_=   {node: graph[node][:] for node in graph}

						while len(lowerCAmelCase_				) > 2:
												# Choose a random edge.
												UpperCAmelCase_=   random.choice(list(graph_copy.keys()				)				)
												UpperCAmelCase_=   random.choice(graph_copy[u]				)

												# Contract edge (u, v) to new node uv
												UpperCAmelCase_=   u + v
												UpperCAmelCase_=   list(set(graph_copy[u] + graph_copy[v]				)				)
												uv_neighbors.remove(lowerCAmelCase_				)
												uv_neighbors.remove(lowerCAmelCase_				)
												UpperCAmelCase_=   uv_neighbors
												for neighbor in uv_neighbors:
																		graph_copy[neighbor].append(lowerCAmelCase_				)

												UpperCAmelCase_=   set(contracted_nodes[u].union(contracted_nodes[v]				)				)

												# Remove nodes u and v.
												del graph_copy[u]
												del graph_copy[v]
												for neighbor in uv_neighbors:
																		if u in graph_copy[neighbor]:
																								graph_copy[neighbor].remove(lowerCAmelCase_				)
																		if v in graph_copy[neighbor]:
																								graph_copy[neighbor].remove(lowerCAmelCase_				)

    # Find cutset.
						UpperCAmelCase_=   [contracted_nodes[node] for node in graph_copy]
						return {
						    (node, neighbor)
						    for node in groups[0]
						    for neighbor in graph[node]
						    if neighbor in groups[1]
						}


if __name__ == "__main__":
	print(partition_graph(TEST_GRAPH))




