






"""simple docstring"""






def       _A    (__a					,       __a							)				-> str:
    """simple docstring"""






    print('''\nThe shortest path matrix using Floyd Warshall algorithm\n'''							)
    for i in range(__a							):
        for j in range(__a							):
            if dist[i][j] != float('''inf'''							):
                print(int(dist[i][j]							)					,       end='''\t'''							)
            else:
                print('''INF'''					,       end='''\t'''							)
        print()



def       _A    (__a					,       __a							)				-> int:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						int							=	[[float('''inf'''							) for _ in range(__a							)] for _ in range(__a							)]

    for i in range(__a							):
        for j in range(__a							):
            SCREAMING_SNAKE_CASE_   :						List[Any]							=	graph[i][j]

            # check vertex k against all other vertices (i, j)
    for k in range(__a							):
        # looping through rows of graph array
        for i in range(__a							):
            # looping through columns of graph array
            for j in range(__a							):
                if (
                    dist[i][k] != float('''inf'''							)
                    and dist[k][j] != float('''inf'''							)
                    and dist[i][k] + dist[k][j] < dist[i][j]
                ):
                    SCREAMING_SNAKE_CASE_   :						Any							=	dist[i][k] + dist[k][j]

    _print_dist(__a					,       __a							)
    return dist, v


if __name__ == "__main__":
  UpperCAmelCase_     :				List[str]         =				int(input("""Enter number of vertices: """))
  UpperCAmelCase_     :				List[str]         =				int(input("""Enter number of edges: """))

  UpperCAmelCase_     :				Optional[Any]         =				[[float("""inf""") for i in range(v)] for j in range(v)]

  for i in range(v):
    UpperCAmelCase_     :				Optional[int]         =				0.0

    # src and dst are indices that must be within the array size graph[e][v]
    # failure to follow this will result in an error
  for i in range(e):
    print("""\nEdge """, i + 1)
    UpperCAmelCase_     :				Tuple         =				int(input("""Enter source:"""))
    UpperCAmelCase_     :				int         =				int(input("""Enter destination:"""))
    UpperCAmelCase_     :				Tuple         =				float(input("""Enter weight:"""))
    UpperCAmelCase_     :				Any         =				weight

  floyd_warshall(graph, v)

  # Example Input
  # Enter number of vertices: 3
  # Enter number of edges: 2

  # # generated graph from vertex and edge inputs
  # [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
  # [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

  # specify source, destination and weight for edge #1
  # Edge  1
  # Enter source:1
  # Enter destination:2
  # Enter weight:2

  # specify source, destination and weight for edge #2
  # Edge  2
  # Enter source:2
  # Enter destination:1
  # Enter weight:1

  # # Expected Output from the vertice, edge and src, dst, weight inputs!!
  # 0		INF	INF
  # INF	0	2
  # INF	1	0










"""simple docstring"""






import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser



def       _A    (__a							)				-> Optional[int]:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	{}
    SCREAMING_SNAKE_CASE_   :						List[Any]							=	tokenizer(example['''content''']					,       truncation=__a							)['''input_ids''']
    SCREAMING_SNAKE_CASE_   :						List[Any]							=	len(example['''content''']							) / len(output['''input_ids''']							)
    return output


UpperCAmelCase_     :				Tuple         =				HfArgumentParser(PretokenizationArguments)
UpperCAmelCase_     :				Tuple         =				parser.parse_args()
if args.num_workers is None:
  UpperCAmelCase_     :				Tuple         =				multiprocessing.cpu_count()
UpperCAmelCase_     :				str         =				AutoTokenizer.from_pretrained(args.tokenizer_dir)

UpperCAmelCase_     :				Tuple         =				time.time()
UpperCAmelCase_     :				List[Any]         =				load_dataset(args.dataset_name, split="""train""")
print(f'''Dataset loaded in {time.time()-t_start:.2f}s''')

UpperCAmelCase_     :				Dict         =				time.time()
UpperCAmelCase_     :				Dict         =				ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        """repo_name""",
        """path""",
        """copies""",
        """size""",
        """content""",
        """license""",
        """hash""",
        """line_mean""",
        """line_max""",
        """alpha_frac""",
        """autogenerated""",
    ],
)
print(f'''Dataset tokenized in {time.time()-t_start:.2f}s''')

UpperCAmelCase_     :				str         =				time.time()
ds.push_to_hub(args.tokenized_data_repo)





print(f'''Data pushed to the hub in {time.time()-t_start:.2f}s''')


