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类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)
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())
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
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)
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)