From f835ac902ce3cae4e1c43136c4510e3e9c0a31e6 Mon Sep 17 00:00:00 2001 From: zach dwiel Date: Wed, 24 Oct 2018 10:52:18 -0400 Subject: [PATCH] fix renaming: save_checkpoint_sec -> checkpoint_save_secs --- rl_coach/base_parameters.py | 6 +++--- rl_coach/coach.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/rl_coach/base_parameters.py b/rl_coach/base_parameters.py index 1bbb53a..028b649 100644 --- a/rl_coach/base_parameters.py +++ b/rl_coach/base_parameters.py @@ -416,13 +416,13 @@ class AgentParameters(Parameters): class TaskParameters(Parameters): def __init__(self, framework_type: str='tensorflow', evaluate_only: bool=False, use_cpu: bool=False, - experiment_path='/tmp', seed=None, save_checkpoint_secs=None): + experiment_path='/tmp', seed=None, checkpoint_save_secs=None): """ :param framework_type: deep learning framework type. currently only tensorflow is supported :param evaluate_only: the task will be used only for evaluating the model :param use_cpu: use the cpu for this task :param experiment_path: the path to the directory which will store all the experiment outputs - :param save_checkpoint_secs: the number of seconds between each checkpoint saving + :param checkpoint_save_secs: the number of seconds between each checkpoint saving :param seed: a seed to use for the random numbers generator """ self.framework_type = framework_type @@ -430,7 +430,7 @@ class TaskParameters(Parameters): self.evaluate_only = evaluate_only self.use_cpu = use_cpu self.experiment_path = experiment_path - self.save_checkpoint_secs = save_checkpoint_secs + self.checkpoint_save_secs = checkpoint_save_secs self.seed = seed diff --git a/rl_coach/coach.py b/rl_coach/coach.py index be7c81e..e057a77 100644 --- a/rl_coach/coach.py +++ b/rl_coach/coach.py @@ -350,7 +350,7 @@ def main(): experiment_path=args.experiment_path, seed=args.seed, use_cpu=args.use_cpu, - save_checkpoint_secs=args.save_checkpoint_secs) + checkpoint_save_secs=args.checkpoint_save_secs) task_parameters.__dict__ = add_items_to_dict(task_parameters.__dict__, args.__dict__) start_graph(graph_manager=graph_manager, task_parameters=task_parameters)