

lowerCAmelCase__								=		[
    [0, 1_6, 1_3, 0, 0, 0],
    [0, 0, 1_0, 1_2, 0, 0],
    [0, 4, 0, 0, 1_4, 0],
    [0, 0, 9, 0, 0, 2_0],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]






def 					lowerCamelCase_     (							UpperCAmelCase_							:     Union[str, Any]							,       UpperCAmelCase_							:     str							,       UpperCAmelCase_							:     Any							,       UpperCAmelCase_							:     Any	)						->				List[Any]:




	'''simple docstring'''




	_UpperCamelCase   :		List[Any]			=						[False] * len(UpperCAmelCase_	)
	_UpperCamelCase   :		str			=						[s]
	_UpperCamelCase   :		int			=						True

	while queue:
		_UpperCamelCase   :		Any			=						queue.pop(0	)
		for ind in range(len(graph[u]	)	):
			if visited[ind] is False and graph[u][ind] > 0:
				queue.append(UpperCAmelCase_	)
				_UpperCamelCase   :		Optional[Any]			=						True
				_UpperCamelCase   :		List[str]			=						u

	return visited[t]






def 					lowerCamelCase_     (							UpperCAmelCase_							:     Optional[int]							,       UpperCAmelCase_							:     Optional[Any]							,       UpperCAmelCase_							:     Dict	)						->				str:




	'''simple docstring'''




	_UpperCamelCase   :		Union[str, Any]			=						[-1] * (len(UpperCAmelCase_	))
	_UpperCamelCase   :		Union[str, Any]			=						0
	_UpperCamelCase   :		Optional[int]			=						[]
	_UpperCamelCase   :		Union[str, Any]			=						[i[:] for i in graph]  # Record original cut, copy.
	while bfs(UpperCAmelCase_							,       UpperCAmelCase_							,       UpperCAmelCase_							,       UpperCAmelCase_	):
		_UpperCamelCase   :		Any			=						float('Inf'	)
		_UpperCamelCase   :		Tuple			=						sink

		while s != source:
			# Find the minimum value in select path
			_UpperCamelCase   :		Optional[Any]			=						min(UpperCAmelCase_							,       graph[parent[s]][s]	)
			_UpperCamelCase   :		Tuple			=						parent[s]

		max_flow += path_flow
		_UpperCamelCase   :		Optional[Any]			=						sink

		while v != source:
			_UpperCamelCase   :		Dict			=						parent[v]
			graph[u][v] -= path_flow
			graph[v][u] += path_flow
			_UpperCamelCase   :		List[str]			=						parent[v]

	for i in range(len(UpperCAmelCase_	)	):
		for j in range(len(graph[0]	)	):
			if graph[i][j] == 0 and temp[i][j] > 0:
				res.append((i, j)	)

	return res


if __name__ == "__main__":
							print(mincut(test_graph, source=0, sink=5))







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__								=		logging.get_logger(__name__)

lowerCAmelCase__								=		{
    """RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-430m-pile""": """https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-1b5-pile""": """https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-3b-pile""": """https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-7b-pile""": """https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-14b-pile""": """https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json""",
    """RWKV/rwkv-raven-1b5""": """https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json""",
    """RWKV/rwkv-raven-3b""": """https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json""",
    """RWKV/rwkv-raven-7b""": """https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json""",
    """RWKV/rwkv-raven-14b""": """https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json""",
}







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




		a__					       =  "rwkv"
		a__					       =  {"max_position_embeddings": "context_length"}


		def __init__(				self	,       __snake_case=5_02_77	,       __snake_case=10_24	,       __snake_case=40_96	,       __snake_case=32	,       __snake_case=None	,       __snake_case=None	,       __snake_case=1e-5	,       __snake_case=0	,       __snake_case=0	,       __snake_case=6	,       __snake_case=False	,       __snake_case=True	,       **__snake_case	,       ):
			_UpperCamelCase   :		str			=						vocab_size
			_UpperCamelCase   :		int			=						context_length
			_UpperCamelCase   :		Tuple			=						hidden_size
			_UpperCamelCase   :		Tuple			=						num_hidden_layers
			_UpperCamelCase   :		Dict			=						attention_hidden_size if attention_hidden_size is not None else hidden_size
			_UpperCamelCase   :		Tuple			=						intermediate_size if intermediate_size is not None else 4 * hidden_size
			_UpperCamelCase   :		Union[str, Any]			=						layer_norm_epsilon
			_UpperCamelCase   :		Dict			=						rescale_every
			_UpperCamelCase   :		Optional[Any]			=						use_cache

			_UpperCamelCase   :		str			=						bos_token_id
			_UpperCamelCase   :		Optional[Any]			=						eos_token_id

			super().__init__(
			    tie_word_embeddings=__snake_case	,       bos_token_id=__snake_case	,       eos_token_id=__snake_case	,       **__snake_case)




