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