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Python registry.list_problems方法代码示例

本文整理汇总了Python中tensor2tensor.utils.registry.list_problems方法的典型用法代码示例。如果您正苦于以下问题:Python registry.list_problems方法的具体用法?Python registry.list_problems怎么用?Python registry.list_problems使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在tensor2tensor.utils.registry的用法示例。


在下文中一共展示了registry.list_problems方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: main

# 需要导入模块: from tensor2tensor.utils import registry [as 别名]
# 或者: from tensor2tensor.utils.registry import list_problems [as 别名]
def main(_):

  tf.gfile.MakeDirs(FLAGS.data_dir)
  tf.gfile.MakeDirs(FLAGS.tmp_dir)

  # Create problem if not already defined
  problem_name = "gym_discrete_problem_with_agent_on_%s" % FLAGS.game
  if problem_name not in registry.list_problems():
    gym_env.register_game(FLAGS.game)

  # Generate
  tf.logging.info("Running %s environment for %d steps for trajectories.",
                  FLAGS.game, FLAGS.num_env_steps)
  problem = registry.problem(problem_name)
  problem.settable_num_steps = FLAGS.num_env_steps
  problem.settable_eval_phase = FLAGS.eval
  problem.generate_data(FLAGS.data_dir, FLAGS.tmp_dir)

  # Log stats
  if problem.statistics.number_of_dones:
    mean_reward = (problem.statistics.sum_of_rewards /
                   problem.statistics.number_of_dones)
    tf.logging.info("Mean reward: %.2f, Num dones: %d",
                    mean_reward,
                    problem.statistics.number_of_dones) 
开发者ID:mlperf,项目名称:training_results_v0.5,代码行数:27,代码来源:datagen_with_agent.py

示例2: available

# 需要导入模块: from tensor2tensor.utils import registry [as 别名]
# 或者: from tensor2tensor.utils.registry import list_problems [as 别名]
def available():
  return sorted(registry.list_problems()) 
开发者ID:akzaidi,项目名称:fine-lm,代码行数:4,代码来源:problems.py

示例3: available

# 需要导入模块: from tensor2tensor.utils import registry [as 别名]
# 或者: from tensor2tensor.utils.registry import list_problems [as 别名]
def available():
  return sorted(registry.list_problems())


# Import problem modules 
开发者ID:tensorflow,项目名称:tensor2tensor,代码行数:7,代码来源:problems_colab.py

示例4: main

# 需要导入模块: from tensor2tensor.utils import registry [as 别名]
# 或者: from tensor2tensor.utils.registry import list_problems [as 别名]
def main(_):
  usr_dir.import_usr_dir(FLAGS.t2t_usr_dir)

  # Calculate the list of problems to generate.
  problems = sorted(
      list(_SUPPORTED_PROBLEM_GENERATORS) + registry.list_problems())
  for exclude in FLAGS.exclude_problems.split(","):
    if exclude:
      problems = [p for p in problems if exclude not in p]
  if FLAGS.problem and FLAGS.problem[-1] == "*":
    problems = [p for p in problems if p.startswith(FLAGS.problem[:-1])]
  elif FLAGS.problem:
    problems = [p for p in problems if p == FLAGS.problem]
  else:
    problems = []

  # Remove TIMIT if paths are not given.
  if not FLAGS.timit_paths:
    problems = [p for p in problems if "timit" not in p]
  # Remove parsing if paths are not given.
  if not FLAGS.parsing_path:
    problems = [p for p in problems if "parsing_english_ptb" not in p]

  if not problems:
    problems_str = "\n  * ".join(
        sorted(list(_SUPPORTED_PROBLEM_GENERATORS) + registry.list_problems()))
    error_msg = ("You must specify one of the supported problems to "
                 "generate data for:\n  * " + problems_str + "\n")
    error_msg += ("TIMIT and parsing need data_sets specified with "
                  "--timit_paths and --parsing_path.")
    raise ValueError(error_msg)

  if not FLAGS.data_dir:
    FLAGS.data_dir = tempfile.gettempdir()
    tf.logging.warning("It is strongly recommended to specify --data_dir. "
                       "Data will be written to default data_dir=%s.",
                       FLAGS.data_dir)
  FLAGS.data_dir = os.path.expanduser(FLAGS.data_dir)
  tf.gfile.MakeDirs(FLAGS.data_dir)

  tf.logging.info("Generating problems:\n%s"
                  % registry.display_list_by_prefix(problems,
                                                    starting_spaces=4))
  if FLAGS.only_list:
    return
  for problem in problems:
    set_random_seed()

    if problem in _SUPPORTED_PROBLEM_GENERATORS:
      generate_data_for_problem(problem)
    else:
      generate_data_for_registered_problem(problem) 
开发者ID:akzaidi,项目名称:fine-lm,代码行数:54,代码来源:t2t_datagen.py

示例5: main

# 需要导入模块: from tensor2tensor.utils import registry [as 别名]
# 或者: from tensor2tensor.utils.registry import list_problems [as 别名]
def main(_):
  usr_dir.import_usr_dir(FLAGS.t2t_usr_dir)

  # Calculate the list of problems to generate.
  problems = sorted(
      list(_SUPPORTED_PROBLEM_GENERATORS) + registry.list_problems())
  for exclude in FLAGS.exclude_problems.split(","):
    if exclude:
      problems = [p for p in problems if exclude not in p]
  if FLAGS.problem and FLAGS.problem[-1] == "*":
    problems = [p for p in problems if p.startswith(FLAGS.problem[:-1])]
  elif FLAGS.problem and "," in FLAGS.problem:
    problems = [p for p in problems if p in FLAGS.problem.split(",")]
  elif FLAGS.problem:
    problems = [p for p in problems if p == FLAGS.problem]
  else:
    problems = []

  # Remove TIMIT if paths are not given.
  if getattr(FLAGS, "timit_paths", None):
    problems = [p for p in problems if "timit" not in p]
  # Remove parsing if paths are not given.
  if getattr(FLAGS, "parsing_path", None):
    problems = [p for p in problems if "parsing_english_ptb" not in p]

  if not problems:
    problems_str = "\n  * ".join(
        sorted(list(_SUPPORTED_PROBLEM_GENERATORS) + registry.list_problems()))
    error_msg = ("You must specify one of the supported problems to "
                 "generate data for:\n  * " + problems_str + "\n")
    error_msg += ("TIMIT and parsing need data_sets specified with "
                  "--timit_paths and --parsing_path.")
    raise ValueError(error_msg)

  if not FLAGS.data_dir:
    FLAGS.data_dir = tempfile.gettempdir()
    tf.logging.warning("It is strongly recommended to specify --data_dir. "
                       "Data will be written to default data_dir=%s.",
                       FLAGS.data_dir)
  FLAGS.data_dir = os.path.expanduser(FLAGS.data_dir)
  tf.gfile.MakeDirs(FLAGS.data_dir)

  tf.logging.info("Generating problems:\n%s"
                  % registry.display_list_by_prefix(problems,
                                                    starting_spaces=4))
  if FLAGS.only_list:
    return
  for problem in problems:
    set_random_seed()

    if problem in _SUPPORTED_PROBLEM_GENERATORS:
      generate_data_for_problem(problem)
    else:
      generate_data_for_registered_problem(problem) 
开发者ID:mlperf,项目名称:training_results_v0.5,代码行数:56,代码来源:t2t_datagen.py


注:本文中的tensor2tensor.utils.registry.list_problems方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。