


from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
UpperCAmelCase_      : str  					=       HfArgumentParser(InitializationArguments)
UpperCAmelCase_      : str  					=       parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
UpperCAmelCase_      : str  					=       AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
UpperCAmelCase_      : Optional[Any]  					=       {
    'vocab_size': len(tokenizer),
    'scale_attn_by_inverse_layer_idx': True,
    'reorder_and_upcast_attn': True,
}

# Load model config (GPT-2 large in this case)
UpperCAmelCase_      : Dict  					=       AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
UpperCAmelCase_      : Optional[int]  					=       AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)






def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__   , lowercase__	)						->	Union[str, Any]:

		'''simple docstring'''







		__lowercase=			[False] * len(lowercase__	)
		__lowercase=			[]
		queue.append(lowercase__	)
		__lowercase=			True

		while queue:
				__lowercase=			queue.pop(0	)
				for ind in range(len(graph[u]	)	):
						if visited[ind] is False and graph[u][ind] > 0:
								queue.append(lowercase__	)
								__lowercase=			True
								__lowercase=			u

		return visited[t]







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__	)						->	int:

		'''simple docstring'''







		__lowercase=			[-1] * (len(lowercase__	))
		__lowercase=			0
		while bfs(lowercase__   , lowercase__   , lowercase__   , lowercase__	):
				__lowercase=			float('Inf'	)
				__lowercase=			sink

				while s != source:
						# Find the minimum value in select path
						__lowercase=			min(lowercase__   , graph[parent[s]][s]	)
						__lowercase=			parent[s]

				max_flow += path_flow
				__lowercase=			sink

				while v != source:
						__lowercase=			parent[v]
						graph[u][v] -= path_flow
						graph[v][u] += path_flow
						__lowercase=			parent[v]
		return max_flow


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],
]

lowerCAmelCase       ,lowerCAmelCase           =		0, 5
print(ford_fulkerson(graph, source, sink))






