test_PPT.py

import argparse
from trainer import test_final_trajectory as trainer_ppt

import numpy as np
import random
import torch


def prepare_seed(rand_seed):
	np.random.seed(rand_seed)
	random.seed(rand_seed)
	torch.manual_seed(rand_seed)
	torch.cuda.manual_seed_all(rand_seed)

    
def parse_config():
    parser = argparse.ArgumentParser(description='test')
    parser.add_argument("--cuda", default=True)

    parser.add_argument("--past_len", type=int, default=8, help="length of past (in timesteps)")
    parser.add_argument("--future_len", type=int, default=12, help="length of future (in timesteps)")
    parser.add_argument("--dim_embedding_key", type=int, default=24)
    parser.add_argument("--data_scale", type=float, default=1)
    parser.add_argument("--data_scale_old", type=float, default=1.86)
    parser.add_argument("--train_b_size", type=int, default=512)
    parser.add_argument("--test_b_size", type=int, default=4096)
    parser.add_argument("--time_thresh", type=int, default=0)
    parser.add_argument("--dist_thresh", type=int, default=100)
    
    parser.add_argument('--gpu', type=int, default=0)
    parser.add_argument("--model_Pretrain", default='./training/...')

    parser.add_argument("--reproduce", default=False)
    

    parser.add_argument("--dataset_file", default="SDD", help="dataset file")
    parser.add_argument("--dataset_name", default="sdd", help="dataset file")
    parser.add_argument("--data_scene", default="eth", help="dataset file")
    parser.add_argument("--info", type=str, default='', help='Name of training. '
                                                             'It will be used in tensorboard log and test folder')
    return parser.parse_args()


def main(config):
    if config.reproduce:
        config.model_Pretrain = './training/Pretrained_Models/SDD/model_ALL'
        print(config.model_Pretrain)
        t = trainer_ppt.Trainer(config)
        t.fit()
    else:
        print(config.model_Pretrain)
        t = trainer_ppt.Trainer(config)
        t.fit()


if __name__ == "__main__":
    config = parse_config()
    main(config)