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Fix cmd line arguments handling (#68)

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* refactoring the merging of the task parameters and the command line parameters
* removing some unused command line arguments
* fix for saving checkpoints when not passing through coach.py
This commit is contained in:
Itai Caspi
2018-11-07 15:47:02 +02:00
committed by GitHub
parent 93571306c3
commit e7a91b4dc3
4 changed files with 53 additions and 50 deletions
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18
rl_coach/base_parameters.py
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@@ -432,14 +432,17 @@ class AgentParameters(Parameters):
class TaskParameters(Parameters):
def __init__(self, framework_type: Frameworks=Frameworks.tensorflow, evaluate_only: bool=False, use_cpu: bool=False,
experiment_path='/tmp', seed=None, checkpoint_save_secs=None):
experiment_path='/tmp', seed=None, checkpoint_save_secs=None, checkpoint_restore_dir=None,
checkpoint_save_dir=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 checkpoint_save_secs: the number of seconds between each checkpoint saving
:param seed: a seed to use for the random numbers generator
:param checkpoint_save_secs: the number of seconds between each checkpoint saving
:param checkpoint_restore_dir: the directory to restore the checkpoints from
:param checkpoint_save_dir: the directory to store the checkpoints in
"""
self.framework_type = framework_type
self.task_index = 0 # TODO: not really needed
@@ -447,6 +450,8 @@ class TaskParameters(Parameters):
self.use_cpu = use_cpu
self.experiment_path = experiment_path
self.checkpoint_save_secs = checkpoint_save_secs
self.checkpoint_restore_dir = checkpoint_restore_dir
self.checkpoint_save_dir = checkpoint_save_dir
self.seed = seed
@@ -454,7 +459,8 @@ class DistributedTaskParameters(TaskParameters):
def __init__(self, framework_type: Frameworks, parameters_server_hosts: str, worker_hosts: str, job_type: str,
task_index: int, evaluate_only: bool=False, num_tasks: int=None,
num_training_tasks: int=None, use_cpu: bool=False, experiment_path=None, dnd=None,
shared_memory_scratchpad=None, seed=None):
shared_memory_scratchpad=None, seed=None, checkpoint_save_secs=None, checkpoint_restore_dir=None,
checkpoint_save_dir=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
@@ -469,9 +475,13 @@ class DistributedTaskParameters(TaskParameters):
:param experiment_path: the path to the directory which will store all the experiment outputs
:param dnd: an external DND to use for NEC. This is a workaround needed for a shared DND not using the scratchpad.
:param seed: a seed to use for the random numbers generator
:param checkpoint_save_secs: the number of seconds between each checkpoint saving
:param checkpoint_restore_dir: the directory to restore the checkpoints from
:param checkpoint_save_dir: the directory to store the checkpoints in
"""
super().__init__(framework_type=framework_type, evaluate_only=evaluate_only, use_cpu=use_cpu,
experiment_path=experiment_path, seed=seed)
experiment_path=experiment_path, seed=seed, checkpoint_save_secs=checkpoint_save_secs,
checkpoint_restore_dir=checkpoint_restore_dir, checkpoint_save_dir=checkpoint_save_dir)
self.parameters_server_hosts = parameters_server_hosts
self.worker_hosts = worker_hosts
self.job_type = job_type