def prepare_dirs(
signature='unspecified_signature',
config_name='unspecified_config_name',
exp_uid='unspecified_exp_uid',
):
"""Prepare saving and sampling direcotories for training.
Args:
signature: A string of signature of model such as `joint_model`.
config_name: A string representing the name of config for joint model.
exp_uid: A string representing the unique id of experiment to be used in
joint model.
Returns:
A tuple of (save_dir, sample_dir). They are strings and are paths to the
directory for saving checkpoints / summaries and path to the directory
for saving samplings, respectively.
"""
model_uid = common.get_model_uid(config_name, exp_uid)
local_base_path = os.path.join(common.get_default_scratch(), signature)
save_dir = os.path.join(local_base_path, 'ckpts', model_uid)
tf.gfile.MakeDirs(save_dir)
sample_dir = os.path.join(local_base_path, 'sample', model_uid)
tf.gfile.MakeDirs(sample_dir)
return save_dir, sample_dir
def prepare_dirs(
signature='unspecified_signature',
config_name='unspecified_config_name',
exp_uid='unspecified_exp_uid',
):
"""Prepare saving and sampling direcotories for training.
Args:
signature: A string of signature of model such as `joint_model`.
config_name: A string representing the name of config for joint model.
exp_uid: A string representing the unique id of experiment to be used in
joint model.
Returns:
A tuple of (save_dir, sample_dir). They are strings and are paths to the
directory for saving checkpoints / summaries and path to the directory
for saving samplings, respectively.
"""
model_uid = common.get_model_uid(config_name, exp_uid)
local_base_path = os.path.join(common.get_default_scratch(), signature)
save_dir = os.path.join(local_base_path, 'ckpts', model_uid)
tf.gfile.MakeDirs(save_dir)
sample_dir = os.path.join(local_base_path, 'sample', model_uid)
tf.gfile.MakeDirs(sample_dir)
return save_dir, sample_dir