train_linear.py

from utils.preprocess import greyscale
from utils.wrappers import PreproWrapper, MaxAndSkipEnv

from linear_schedule import LinearExploration, LinearSchedule
from linear_dqn import Linear

from configs.linear import config
import rewards
import read_midis
import numpy as np

if __name__ == '__main__':
    env = rewards.MusicEnv(midigold=np.array(read_midis.load_dataset("data/dataset_100.p")))
    
    # exploration strategy
    exp_schedule = LinearExploration(env, config.eps_begin, 
            config.eps_end, config.eps_nsteps)

    # learning rate schedule
    lr_schedule  = LinearSchedule(config.lr_begin, config.lr_end,
            config.lr_nsteps)

    # train model
    model = Linear(env, config)
    model.run(exp_schedule, lr_schedule)