






# Usage:
# ./gen-card-allenai-wmt19.py

import os
from pathlib import Path

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__			,					UpperCAmelCase__			,					UpperCAmelCase__						) ->       Optional[int]:
  UpperCamelCase_:      Optional[Any]					   =       {
      '''en''': '''Machine learning is great, isn\'t it?''',
      '''ru''': '''Машинное обучение - это здорово, не так ли?''',
      '''de''': '''Maschinelles Lernen ist großartig, nicht wahr?''',
  }

  # BLUE scores as follows:
  # "pair": [fairseq, transformers]
  UpperCamelCase_:      List[Any]					   =       {
      '''wmt19-de-en-6-6-base''': [0, 3_8.3_7],
      '''wmt19-de-en-6-6-big''': [0, 3_9.9_0],
  }
  UpperCamelCase_:      List[Any]					   =       F'''{src_lang}-{tgt_lang}'''

  UpperCamelCase_:      Union[str, Any]					   =       F'''\n---\n\nlanguage:\n- {src_lang}\n- {tgt_lang}\nthumbnail:\ntags:\n- translation\n- wmt19\n- allenai\nlicense: apache-2.0\ndatasets:\n- wmt19\nmetrics:\n- bleu\n---\n\n# FSMT\n\n## Model description\n\nThis is a ported version of fairseq-based [wmt19 transformer](https://github.com/jungokasai/deep-shallow/) for {src_lang}-{tgt_lang}.\n\nFor more details, please, see [Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation](https://arxiv.org/abs/2006.10369).\n\n2 models are available:\n\n* [wmt19-de-en-6-6-big](https://huggingface.co/allenai/wmt19-de-en-6-6-big)\n* [wmt19-de-en-6-6-base](https://huggingface.co/allenai/wmt19-de-en-6-6-base)\n\n\n## Intended uses & limitations\n\n#### How to use\n\n```python\nfrom transformers import FSMTForConditionalGeneration, FSMTTokenizer\nmname = "allenai/{model_name}"\ntokenizer = FSMTTokenizer.from_pretrained(mname)\nmodel = FSMTForConditionalGeneration.from_pretrained(mname)\n\ninput = "{texts[src_lang]}"\ninput_ids = tokenizer.encode(input, return_tensors="pt")\noutputs = model.generate(input_ids)\ndecoded = tokenizer.decode(outputs[0], skip_special_tokens=True)\nprint(decoded) # {texts[tgt_lang]}\n\n```\n\n#### Limitations and bias\n\n\n## Training data\n\nPretrained weights were left identical to the original model released by allenai. For more details, please, see the [paper](https://arxiv.org/abs/2006.10369).\n\n## Eval results\n\nHere are the BLEU scores:\n\nmodel   |  transformers\n-------|---------\n{model_name}  |  {scores[model_name][1]}\n\nThe score was calculated using this code:\n\n```bash\ngit clone https://github.com/huggingface/transformers\ncd transformers\nexport PAIR={pair}\nexport DATA_DIR=data/$PAIR\nexport SAVE_DIR=data/$PAIR\nexport BS=8\nexport NUM_BEAMS=5\nmkdir -p $DATA_DIR\nsacrebleu -t wmt19 -l $PAIR --echo src > $DATA_DIR/val.source\nsacrebleu -t wmt19 -l $PAIR --echo ref > $DATA_DIR/val.target\necho $PAIR\nPYTHONPATH="src:examples/seq2seq" python examples/seq2seq/run_eval.py allenai/{model_name} $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation --num_beams $NUM_BEAMS\n```\n\n## Data Sources\n\n- [training, etc.](http://www.statmt.org/wmt19/)\n- [test set](http://matrix.statmt.org/test_sets/newstest2019.tgz?1556572561)\n\n\n### BibTeX entry and citation info\n\n```\n@misc{{kasai2020deep,\n    title={{Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation}},\n    author={{Jungo Kasai and Nikolaos Pappas and Hao Peng and James Cross and Noah A. Smith}},\n    year={{2020}},\n    eprint={{2006.10369}},\n    archivePrefix={{arXiv}},\n    primaryClass={{cs.CL}}\n}}\n```\n\n'''
  model_card_dir.mkdir(parents=snake_case_			,					exist_ok=snake_case_						)
  UpperCamelCase_:      Any					   =       os.path.join(snake_case_			,					'README.md'						)
  print(F'''Generating {path}'''						)
  with open(snake_case_			,					'w'			,					encoding='utf-8'						) as f:
    f.write(snake_case_						)


# make sure we are under the root of the project
A_	:	Union[str, Any]				=				Path(__file__).resolve().parent.parent.parent
A_	:	Union[str, Any]				=				repo_dir / "model_cards"

for model_name in ["wmt19-de-en-6-6-base", "wmt19-de-en-6-6-big"]:
   A_	:	Any				=				model_cards_dir / "allenai" / model_name
   write_model_card(model_card_dir, src_lang='de', tgt_lang='en', model_name=model_name)













from collections import deque

def 						snake_case      (UpperCAmelCase__						) ->       Any:
  return input(UpperCAmelCase__						).strip().split(' '						)

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       dict[int, list[int]]:
  UpperCamelCase_:      dict[int, list[int]]					   =       {}
  for i in range(UpperCAmelCase__						):
    UpperCamelCase_:      str					   =       []

  for e in range(UpperCAmelCase__						):
    UpperCamelCase_   ,UpperCamelCase_:      List[Any]					   =       (int(UpperCAmelCase__						) for i in _input(F'''Edge {e + 1}: <node1> <node2> '''						))
    graph[x].append(UpperCAmelCase__						)
  return graph

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       dict[int, list[int]]:
  UpperCamelCase_:      dict[int, list[int]]					   =       {}
  for i in range(UpperCAmelCase__						):
    UpperCamelCase_:      Tuple					   =       []

  for e in range(UpperCAmelCase__						):
    UpperCamelCase_   ,UpperCamelCase_:      str					   =       (int(UpperCAmelCase__						) for i in _input(F'''Edge {e + 1}: <node1> <node2> '''						))
    graph[x].append(UpperCAmelCase__						)
    graph[y].append(UpperCAmelCase__						)
  return graph

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       dict[int, list[tuple[int, int]]]:
  UpperCamelCase_:      dict[int, list[tuple[int, int]]]					   =       {}
  for i in range(UpperCAmelCase__						):
    UpperCamelCase_:      List[Any]					   =       []

  for e in range(UpperCAmelCase__						):
    UpperCamelCase_   ,UpperCamelCase_   ,UpperCamelCase_:      List[str]					   =       (int(UpperCAmelCase__						) for i in _input(F'''Edge {e + 1}: <node1> <node2> <weight> '''						))
    graph[x].append((y, w)						)
    graph[y].append((x, w)						)
  return graph


if __name__ == "__main__":
   A_			,				A_	:	str				=				(int(i) for i in _input('Number of nodes and edges: '))

   A_	:	str				=				int(
       _input(
           'Press 1 or 2 or 3 \n'
           '1. Unweighted directed \n'
           '2. Unweighted undirected \n'
           '3. Weighted undirected \n'
       )[0]
   )

   A_	:	List[str]				=				{
       1: initialize_unweighted_directed_graph,
       2: initialize_unweighted_undirected_graph,
       3: initialize_weighted_undirected_graph,
   }[graph_choice](n, m)

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       Union[str, Any]:
  UpperCamelCase_   ,UpperCamelCase_:      int					   =       {s}, [s]
  print(UpperCAmelCase__						)
  while _s:
    UpperCamelCase_:      Optional[Any]					   =       0
    for i in g[_s[-1]]:
      if i not in vis:
        _s.append(UpperCAmelCase__						)
        vis.add(UpperCAmelCase__						)
        UpperCamelCase_:      Any					   =       1
        print(UpperCAmelCase__						)
        break
    if not flag:
      _s.pop()

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       Dict:
  UpperCamelCase_   ,UpperCamelCase_:      int					   =       {s}, deque([s]						)
  print(UpperCAmelCase__						)
  while q:
    UpperCamelCase_:      Dict					   =       q.popleft()
    for v in g[u]:
      if v not in vis:
        vis.add(UpperCAmelCase__						)
        q.append(UpperCAmelCase__						)
        print(UpperCAmelCase__						)

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       int:
  UpperCamelCase_   ,UpperCamelCase_   ,UpperCamelCase_:      Any					   =       {s: 0}, set(), {s: 0}
  while True:
    if len(UpperCAmelCase__						) == len(UpperCAmelCase__						) - 1:
      break
    UpperCamelCase_:      str					   =       1_0_0_0_0_0
    for i in dist:
      if i not in known and dist[i] < mini:
        UpperCamelCase_:      Dict					   =       dist[i]
        UpperCamelCase_:      str					   =       i
    known.add(UpperCAmelCase__						)
    for v in g[u]:
      if v[0] not in known and dist[u] + v[1] < dist.get(v[0]			,					1_0_0_0_0_0						):
        UpperCamelCase_:      Optional[Any]					   =       dist[u] + v[1]
        UpperCamelCase_:      str					   =       u
  for i in dist:
    if i != s:
      print(dist[i]						)

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__=None			,					UpperCAmelCase__=None						) ->       Optional[Any]:
  if q is None:
    UpperCamelCase_:      Optional[Any]					   =       [1]
  if ind is None:
    UpperCamelCase_:      Union[str, Any]					   =       [0] * (len(UpperCAmelCase__						) + 1)  # SInce oth Index is ignored
    for u in g:
      for v in g[u]:
        ind[v] += 1
    UpperCamelCase_:      Optional[int]					   =       deque()
    for i in g:
      if ind[i] == 0:
        q.append(UpperCAmelCase__						)
  if len(UpperCAmelCase__						) == 0:
    return
  UpperCamelCase_:      Dict					   =       q.popleft()
  print(UpperCAmelCase__						)
  for w in g[v]:
    ind[w] -= 1
    if ind[w] == 0:
      q.append(UpperCAmelCase__						)
  topo(UpperCAmelCase__			,					UpperCAmelCase__			,					UpperCAmelCase__						)

def 						snake_case      () ->       str:
  UpperCamelCase_:      Dict					   =       input().strip()
  UpperCamelCase_:      List[str]					   =       []
  for _ in range(UpperCAmelCase__						):
    a.append(map(UpperCAmelCase__			,					input().strip().split()						)						)
  return a, n

def 						snake_case      (UpperCAmelCase__						) ->       Union[str, Any]:
  ((UpperCamelCase_)   ,(UpperCamelCase_)):      Dict					   =       a_and_n
  UpperCamelCase_:      List[str]					   =       list(UpperCAmelCase__						)
  UpperCamelCase_:      int					   =       [[0] * n for i in range(UpperCAmelCase__						)]
  for k in range(UpperCAmelCase__						):
    for i in range(UpperCAmelCase__						):
      for j in range(UpperCAmelCase__						):
        if dist[i][j] > dist[i][k] + dist[k][j]:
          UpperCamelCase_:      Union[str, Any]					   =       dist[i][k] + dist[k][j]
          UpperCamelCase_:      Optional[int]					   =       k
  print(UpperCAmelCase__						)

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       str:
  UpperCamelCase_   ,UpperCamelCase_   ,UpperCamelCase_:      Tuple					   =       {s: 0}, set(), {s: 0}
  while True:
    if len(UpperCAmelCase__						) == len(UpperCAmelCase__						) - 1:
      break
    UpperCamelCase_:      List[str]					   =       1_0_0_0_0_0
    for i in dist:
      if i not in known and dist[i] < mini:
        UpperCamelCase_:      Tuple					   =       dist[i]
        UpperCamelCase_:      Optional[Any]					   =       i
    known.add(UpperCAmelCase__						)
    for v in g[u]:
      if v[0] not in known and v[1] < dist.get(v[0]			,					1_0_0_0_0_0						):
        UpperCamelCase_:      Dict					   =       v[1]
        UpperCamelCase_:      Optional[Any]					   =       u
  return dist

def 						snake_case      () ->       Optional[int]:
  UpperCamelCase_   ,UpperCamelCase_:      Tuple					   =       map(UpperCAmelCase__			,					input().split(' '						)						)
  UpperCamelCase_:      List[str]					   =       []
  for _ in range(UpperCAmelCase__						):
    edges.append(map(UpperCAmelCase__			,					input().split(' '						)						)						)
  return edges, n

def 						snake_case      (UpperCAmelCase__						) ->       Optional[Any]:
  # Sort edges on the basis of distance
  ((UpperCamelCase_)   ,(UpperCamelCase_)):      Optional[Any]					   =       e_and_n
  e.sort(reverse=UpperCAmelCase__			,					key=lambda UpperCAmelCase__						: x[2]						)
  UpperCamelCase_:      str					   =       [{i} for i in range(1			,					n + 1						)]
  while True:
    if len(UpperCAmelCase__						) == 1:
      break
    print(UpperCAmelCase__						)
    UpperCamelCase_:      Any					   =       e.pop()
    for i in range(len(UpperCAmelCase__						)						):
      if x[0] in s[i]:
        break
    for j in range(len(UpperCAmelCase__						)						):
      if x[1] in s[j]:
        if i == j:
          break
        s[j].update(s[i]						)
        s.pop(UpperCAmelCase__						)
        break

def 						snake_case      (UpperCAmelCase__						) ->       Dict:
  UpperCamelCase_:      Tuple					   =       []
  for node in graph:
    if not graph[node]:
      isolated.append(UpperCAmelCase__						)
  return isolated