hom_traj_gen/main.py
Steffen Illium 91ecf157d6 initial
2020-02-13 20:28:20 +01:00

72 lines
3.0 KiB
Python

# Imports
# =============================================================================
import os
from distutils.util import strtobool
from pathlib import Path
from argparse import ArgumentParser
import warnings
from pytorch_lightning import Trainer
from torch.utils.data import DataLoader
from dataset.dataset import TrajData
from lib.utils.config import Config
from lib.utils.logging import Logger
warnings.filterwarnings('ignore', category=FutureWarning)
warnings.filterwarnings('ignore', category=UserWarning)
_ROOT = Path(__file__).parent
# Paramter Configuration
# =============================================================================
# Argument Parser
main_arg_parser = ArgumentParser(description="parser for fast-neural-style")
# Main Parameters
main_arg_parser.add_argument("--main_debug", type=strtobool, default=False, help="")
main_arg_parser.add_argument("--main_eval", type=strtobool, default=False, help="")
main_arg_parser.add_argument("--main_seed", type=int, default=69, help="")
# Data Parameters
main_arg_parser.add_argument("--data_worker", type=int, default=10, help="")
main_arg_parser.add_argument("--data_batchsize", type=int, default=100, help="")
main_arg_parser.add_argument("--data_root", type=str, default='../data/rpoot', help="")
# Transformations
main_arg_parser.add_argument("--transformations_to_tensor", type=strtobool, default=False, help="")
# Transformations
main_arg_parser.add_argument("--train_outpath", type=str, default="output", help="")
main_arg_parser.add_argument("--train_version", type=strtobool, required=False, help="")
main_arg_parser.add_argument("--train_epochs", type=int, default=10, help="")
main_arg_parser.add_argument("--train_batch_size", type=int, default=512, help="")
main_arg_parser.add_argument("--train_lr", type=float, default=0.002, help="")
# Model
main_arg_parser.add_argument("--model_type", type=str, default="LeNetAE", help="")
main_arg_parser.add_argument("--model_activation", type=str, default="relu", help="")
main_arg_parser.add_argument("--model_filters", type=str, default="[32, 16, 4]", help="")
main_arg_parser.add_argument("--model_use_bias", type=strtobool, default=True, help="")
main_arg_parser.add_argument("--model_use_norm", type=strtobool, default=True, help="")
main_arg_parser.add_argument("--model_dropout", type=float, default=0.00, help="")
# Project
main_arg_parser.add_argument("--project_name", type=str, default='traj-gen', help="")
main_arg_parser.add_argument("--project_owner", type=str, default='si11ium', help="")
main_arg_parser.add_argument("--project_neptune_key", type=str, default=os.getenv('NEPTUNE_KEY'), help="")
# Parse it
args = main_arg_parser.parse_args()
config = Config.read_namespace(args)
# Trainer loading
# =============================================================================
trainer = Trainer(logger=Logger(config, debug=True))
if __name__ == '__main__':
print(next(iter(train_dataloader)))
pass