prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Reddit Movie Dialog no longer exists
  **Bug description**
  [Reddit Movie Dialog](https://parl.ai/docs/tasks.html#movie-dialog-reddit) no longer exists.
  
  **Reproduction steps**
  ```
  TrainModel.main(
      # similar to before
      task='empathetic_dialogues,blended_skill_talk,movie_dialog_reddit,convai2,persona_chat', 
      model='transformer/generator',
      model_file='from_pretrained/model',
      
      # initialize with a pretrained model
      init_model='zoo:tutorial_transformer_generator/model',
      
      # arguments we get from the pretrained model.
      # Unfortunately, these must be looked up separately for each model.
      n_heads=16, n_layers=8, n_positions=512, text_truncate=512,
      label_truncate=128, ffn_size=2048, embedding_size=512,
      activation='gelu', variant='xlm',
      dict_lower=True, dict_tokenizer='bpe',
      dict_file='zoo:tutorial_transformer_generator/model.dict',
      learn_positional_embeddings=True,
      
      # some training arguments, specific to this fine-tuning
      # use a small learning rate with ADAM optimizer
      lr=1e-5, optimizer='adam',
      warmup_updates=100,
      # early stopping on perplexity
      validation_metric='ppl',
      # train at most 10 minutes, and validate every 0.25 epochs
      max_train_time=600, validation_every_n_epochs=0.25,
      
      # depend on your gpu. If you have a V100, this is good
      batchsize=12, fp16=True, fp16_impl='mem_efficient',
      
      # speeds up validation
      skip_generation=True,
      
      # helps us cram more examples into our gpu at a time
      dynamic_batching='full',
  )
  ```
  
  **Logs**
  Please paste the command line output:
  
  ```
  ---------------------------------------------------------------------------
  ModuleNotFoundError                       Traceback (most recent call last)
  <ipython-input-39-ff3044de39fe> in <module>()
       36 
       37     # helps us cram more examples into our gpu at a time
  ---> 38     dynamic_batching='full',
       39 )
  
  15 frames
  /usr/lib/python3.6/importlib/_bootstrap.py in _find_and_load_unlocked(name, import_)
  
  ModuleNotFoundError: No module named 'parlai.tasks.movie_dialog_reddit'
  
  ---------------------------------------------------------------------------
  NOTE: If your import is failing due to a missing package, you can
  manually install dependencies using either !pip or !apt.
  
  To view examples of installing some common dependencies, click the
  "Open Examples" button below.
  ---------------------------------------------------------------------------```
  
  
  </issue>
  <code>
  [start of docs/source/generate_task_list.py]
  1 #!/usr/bin/env python3
  2 # Copyright (c) Facebook, Inc. and its affiliates.
  3 # This source code is licensed under the MIT license found in the
  4 # LICENSE file in the root directory of this source tree.
  5 
  6 from parlai.tasks.task_list import task_list
  7 
  8 MASTER = "https://github.com/facebookresearch/ParlAI/tree/master"
  9 
  10 category_order = ['QA', 'Cloze', 'Goal', 'ChitChat', 'Negotiation', 'Visual', 'decanlp']
  11 category_task_list = {x: [] for x in category_order}
  12 
  13 fout = open('task_list.inc', 'w')
  14 
  15 s = "They consist of:  "
  16 for t in category_order:
  17     fout.write(f"1. {t} tasks\n")
  18 fout.write("\n")
  19 
  20 for task_dict in task_list:
  21     tags = task_dict.get('tags', None)
  22     for tag in tags:
  23         if tag in category_task_list:
  24             category_task_list[tag].append(task_dict)
  25 
  26 for num_category, (category, tl) in enumerate(category_task_list.items()):
  27     if num_category != 0:
  28         fout.write("\n-----\n\n")
  29 
  30     fout.write(f'## {category} Tasks\n')
  31 
  32     for task_dict in tl:
  33         id = task_dict.get('id', None)
  34         display_name = task_dict.get('display_name', None)
  35         task = task_dict.get('task', None)
  36         tags = task_dict.get('tags', None)
  37         description = task_dict.get('description', None)
  38         notes = task_dict.get('notes', None)
  39         code_urlend = task[: max(task.find(':'), len(task))]
  40         code_url = f"{MASTER}/parlai/tasks/{code_urlend}"
  41         links = task_dict.get("links", {})
  42         assert isinstance(links, dict), f"task {id} is poorly formatted"
  43         urls = [(k, v) for k, v in links.items()]
  44         urls.append(("code", code_url))
  45 
  46         urls_md = ", ".join(f"[{k}]({v})" for k, v in urls)
  47         fout.write(f"### {display_name}\n")
  48         fout.write(f"_Links_:  {urls_md}\n\n")
  49         if description:
  50             fout.write(description + "\n")
  51         if notes:
  52             fout.write(":::{admonition,note} Notes\n")
  53             fout.write(notes + "\n")
  54             fout.write(":::\n")
  55         fout.write("\n\n")
  56 
  57 fout.close()
  58
  [end of docs/source/generate_task_list.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/docs/source/generate_task_list.py b/docs/source/generate_task_list.py
  --- a/docs/source/generate_task_list.py
  +++ b/docs/source/generate_task_list.py
  @@ -45,6 +45,7 @@
   
           urls_md = ", ".join(f"[{k}]({v})" for k, v in urls)
           fout.write(f"### {display_name}\n")
  +        fout.write(f"_Usage_:  `--task {task}`\n\n")
           fout.write(f"_Links_:  {urls_md}\n\n")
           if description:
               fout.write(description + "\n")
  
verification_info: {"golden_diff": "diff --git a/docs/source/generate_task_list.py b/docs/source/generate_task_list.py\n--- a/docs/source/generate_task_list.py\n+++ b/docs/source/generate_task_list.py\n@@ -45,6 +45,7 @@\n \n         urls_md = \", \".join(f\"[{k}]({v})\" for k, v in urls)\n         fout.write(f\"### {display_name}\\n\")\n+        fout.write(f\"_Usage_:  `--task {task}`\\n\\n\")\n         fout.write(f\"_Links_:  {urls_md}\\n\\n\")\n         if description:\n             fout.write(description + \"\\n\")\n", "issue": "Reddit Movie Dialog no longer exists\n**Bug description**\r\n[Reddit Movie Dialog](https://parl.ai/docs/tasks.html#movie-dialog-reddit) no longer exists.\r\n\r\n**Reproduction steps**\r\n```\r\nTrainModel.main(\r\n    # similar to before\r\n    task='empathetic_dialogues,blended_skill_talk,movie_dialog_reddit,convai2,persona_chat', \r\n    model='transformer/generator',\r\n    model_file='from_pretrained/model',\r\n    \r\n    # initialize with a pretrained model\r\n    init_model='zoo:tutorial_transformer_generator/model',\r\n    \r\n    # arguments we get from the pretrained model.\r\n    # Unfortunately, these must be looked up separately for each model.\r\n    n_heads=16, n_layers=8, n_positions=512, text_truncate=512,\r\n    label_truncate=128, ffn_size=2048, embedding_size=512,\r\n    activation='gelu', variant='xlm',\r\n    dict_lower=True, dict_tokenizer='bpe',\r\n    dict_file='zoo:tutorial_transformer_generator/model.dict',\r\n    learn_positional_embeddings=True,\r\n    \r\n    # some training arguments, specific to this fine-tuning\r\n    # use a small learning rate with ADAM optimizer\r\n    lr=1e-5, optimizer='adam',\r\n    warmup_updates=100,\r\n    # early stopping on perplexity\r\n    validation_metric='ppl',\r\n    # train at most 10 minutes, and validate every 0.25 epochs\r\n    max_train_time=600, validation_every_n_epochs=0.25,\r\n    \r\n    # depend on your gpu. If you have a V100, this is good\r\n    batchsize=12, fp16=True, fp16_impl='mem_efficient',\r\n    \r\n    # speeds up validation\r\n    skip_generation=True,\r\n    \r\n    # helps us cram more examples into our gpu at a time\r\n    dynamic_batching='full',\r\n)\r\n```\r\n\r\n**Logs**\r\nPlease paste the command line output:\r\n\r\n```\r\n---------------------------------------------------------------------------\r\nModuleNotFoundError                       Traceback (most recent call last)\r\n<ipython-input-39-ff3044de39fe> in <module>()\r\n     36 \r\n     37     # helps us cram more examples into our gpu at a time\r\n---> 38     dynamic_batching='full',\r\n     39 )\r\n\r\n15 frames\r\n/usr/lib/python3.6/importlib/_bootstrap.py in _find_and_load_unlocked(name, import_)\r\n\r\nModuleNotFoundError: No module named 'parlai.tasks.movie_dialog_reddit'\r\n\r\n---------------------------------------------------------------------------\r\nNOTE: If your import is failing due to a missing package, you can\r\nmanually install dependencies using either !pip or !apt.\r\n\r\nTo view examples of installing some common dependencies, click the\r\n\"Open Examples\" button below.\r\n---------------------------------------------------------------------------```\r\n\n", "before_files": [{"content": "#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom parlai.tasks.task_list import task_list\n\nMASTER = \"https://github.com/facebookresearch/ParlAI/tree/master\"\n\ncategory_order = ['QA', 'Cloze', 'Goal', 'ChitChat', 'Negotiation', 'Visual', 'decanlp']\ncategory_task_list = {x: [] for x in category_order}\n\nfout = open('task_list.inc', 'w')\n\ns = \"They consist of:  \"\nfor t in category_order:\n    fout.write(f\"1. {t} tasks\\n\")\nfout.write(\"\\n\")\n\nfor task_dict in task_list:\n    tags = task_dict.get('tags', None)\n    for tag in tags:\n        if tag in category_task_list:\n            category_task_list[tag].append(task_dict)\n\nfor num_category, (category, tl) in enumerate(category_task_list.items()):\n    if num_category != 0:\n        fout.write(\"\\n-----\\n\\n\")\n\n    fout.write(f'## {category} Tasks\\n')\n\n    for task_dict in tl:\n        id = task_dict.get('id', None)\n        display_name = task_dict.get('display_name', None)\n        task = task_dict.get('task', None)\n        tags = task_dict.get('tags', None)\n        description = task_dict.get('description', None)\n        notes = task_dict.get('notes', None)\n        code_urlend = task[: max(task.find(':'), len(task))]\n        code_url = f\"{MASTER}/parlai/tasks/{code_urlend}\"\n        links = task_dict.get(\"links\", {})\n        assert isinstance(links, dict), f\"task {id} is poorly formatted\"\n        urls = [(k, v) for k, v in links.items()]\n        urls.append((\"code\", code_url))\n\n        urls_md = \", \".join(f\"[{k}]({v})\" for k, v in urls)\n        fout.write(f\"### {display_name}\\n\")\n        fout.write(f\"_Links_:  {urls_md}\\n\\n\")\n        if description:\n            fout.write(description + \"\\n\")\n        if notes:\n            fout.write(\":::{admonition,note} Notes\\n\")\n            fout.write(notes + \"\\n\")\n            fout.write(\":::\\n\")\n        fout.write(\"\\n\\n\")\n\nfout.close()\n", "path": "docs/source/generate_task_list.py"}]}