
"""simple docstring"""
from __future__ import annotations





def    _lowerCAmelCase    (     lowerCamelCase__							:							list[float],						lowerCamelCase__							:							Tuple				)  ->    Any:
  print(f'''Vertex\tShortest Distance from vertex {src}'''				)
  for i, d in enumerate(lowerCamelCase__				):
    print(f'''{i}\t\t{d}'''				)





def    _lowerCAmelCase    (     lowerCamelCase__							:							list[dict[str, int]],						lowerCamelCase__							:							list[float],						lowerCamelCase__							:							int				)  ->    Tuple:
  for j in range(lowerCamelCase__				):
    _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				str							    = (graph[j][k] for k in ["src", "dst", "weight"])
    if distance[u] != float("inf"				) and distance[u] + w < distance[v]:
      return True
  return False





def    _lowerCAmelCase    (     lowerCamelCase__							:							list[dict[str, int]],						lowerCamelCase__							:							int,						lowerCamelCase__							:							int,						lowerCamelCase__							:							int				)  ->    list[float]:
  _SCREAMING_SNAKE_CASE   :				Tuple							    = [float("inf"				)] * vertex_count
  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = 0.0

  for _ in range(vertex_count - 1				):
    for j in range(lowerCamelCase__				):
      _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Dict							    = (graph[j][k] for k in ["src", "dst", "weight"])

      if distance[u] != float("inf"				) and distance[u] + w < distance[v]:
        _SCREAMING_SNAKE_CASE   :				Dict							    = distance[u] + w

  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = check_negative_cycle(lowerCamelCase__,						lowerCamelCase__,						lowerCamelCase__				)
  if negative_cycle_exists:
    raise Exception("Negative cycle found"				)

  return distance


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      lowercase_       :						Dict     					=	int(input('''Enter number of vertices: ''').strip())
      lowercase_       :						Optional[int]     					=	int(input('''Enter number of edges: ''').strip())

      lowercase_       :						list[dict[str, int]]     					=	[{} for _ in range(E)]

      for i in range(E):
            print('''Edge ''', i + 1)
            lowercase_					,	lowercase_					,	lowercase_       :						str     					=	(
                int(x)
                for x in input('''Enter source, destination, weight: ''').strip().split(''' ''')
            )
            lowercase_       :						str     					=	{'''src''': src, '''dst''': dest, '''weight''': weight}

      lowercase_       :						Tuple     					=	int(input('''\nEnter shortest path source:''').strip())
      lowercase_       :						int     					=	bellman_ford(graph, V, E, source)
      print_distance(shortest_distance, 0)





"""simple docstring"""
import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer





def    _lowerCAmelCase    (     lowerCamelCase__							:							Any,						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							List[str],						lowerCamelCase__							:							Any=1_0_2_4				)  ->    Optional[int]:
  _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				int							    = [], []

  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = list(zip(lowerCamelCase__,						lowerCamelCase__				)				)
  _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				List[Any]							    = sorted_examples[0]

  def is_too_big(lowerCamelCase__							:							List[Any]				):
    return tok(lowerCamelCase__,						return_tensors="pt"				).input_ids.shape[1] > max_tokens

  for src, tgt in tqdm(sorted_examples[1:]				):
    _SCREAMING_SNAKE_CASE   :				int							    = new_src + " " + src
    _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = new_tgt + " " + tgt
    if is_too_big(lowerCamelCase__				) or is_too_big(lowerCamelCase__				):  # cant fit, finalize example
      finished_src.append(lowerCamelCase__				)
      finished_tgt.append(lowerCamelCase__				)
      _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Any							    = src, tgt
    else:  # can fit, keep adding
      _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Optional[Any]							    = cand_src, cand_tgt

    # cleanup
  if new_src:
    assert new_tgt
    finished_src.append(lowerCamelCase__				)
    finished_tgt.append(lowerCamelCase__				)
  return finished_src, finished_tgt





def    _lowerCAmelCase    (     lowerCamelCase__							:							List[str],						lowerCamelCase__							:							Path,						lowerCamelCase__							:							Dict,						lowerCamelCase__							:							List[str]				)  ->    List[Any]:
  _SCREAMING_SNAKE_CASE   :				int							    = Path(lowerCamelCase__				)
  save_path.mkdir(exist_ok=lowerCamelCase__				)
  for split in ["train"]:
    _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Dict							    = data_dir / f'''{split}.source''', data_dir / f'''{split}.target'''
    _SCREAMING_SNAKE_CASE   :				Any							    = [x.rstrip() for x in Path(lowerCamelCase__				).open().readlines()]
    _SCREAMING_SNAKE_CASE   :				int							    = [x.rstrip() for x in Path(lowerCamelCase__				).open().readlines()]
    _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Any							    = pack_examples(lowerCamelCase__,						lowerCamelCase__,						lowerCamelCase__,						lowerCamelCase__				)
    print(f'''packed {split} split from {len(lowerCamelCase__				)} examples -> {len(lowerCamelCase__				)}.'''				)
    Path(save_path / f'''{split}.source'''				).open("w"				).write("\n".join(lowerCamelCase__				)				)
    Path(save_path / f'''{split}.target'''				).open("w"				).write("\n".join(lowerCamelCase__				)				)
  for split in ["val", "test"]:
    _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				int							    = data_dir / f'''{split}.source''', data_dir / f'''{split}.target'''
    shutil.copyfile(lowerCamelCase__,						save_path / f'''{split}.source'''				)
    shutil.copyfile(lowerCamelCase__,						save_path / f'''{split}.target'''				)





def    _lowerCAmelCase    (     )  ->    int:
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = argparse.ArgumentParser()
  parser.add_argument("--tok_name",						type=lowerCamelCase__,						help="like facebook/bart-large-cnn,t5-base, etc."				)
  parser.add_argument("--max_seq_len",						type=lowerCamelCase__,						default=1_2_8				)
  parser.add_argument("--data_dir",						type=lowerCamelCase__				)
  parser.add_argument("--save_path",						type=lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				Tuple							    = parser.parse_args()
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = AutoTokenizer.from_pretrained(args.tok_name				)
  return pack_data_dir(lowerCamelCase__,						Path(args.data_dir				),						args.max_seq_len,						args.save_path				)


if __name__ == "__main__":
      packer_cli()



