cntr += 1
print("removed")
env = SnakeGame()
agent = Agent(gamma = 0.99, epsilon = 1.0, batch_size = 64, n_actions = 4,eps_end = 0.01, input_dims = [16], lr = 0.003)
scores, eps_history, avg_scores, frames = [] , [] , [] ,[] #frames will not be in use
n_games = n_episodes
for i in range(n_games):
score = 0
step = 0
done = False
observation = env.reset()
# frames.append(env.animate(i,step,score))
snake_len = len(env.snake)
frame = env.animate(i,step,score,snake_len)
frame.save(f"{target_folder}/ep{i}step{step}.jpg","jpeg")
while not done:
step += 1
action = agent.choose_action(observation)
observation_, reward, done = env.step(action)
score += reward
agent.store_transition(observation, action, reward, observation_, done)
agent.learn()
observation = observation_
snake_len = len(env.snake)
frame = env.animate(i,step,score,snake_len)
frame.save(f"{target_folder}/ep{i}step{step}.jpg","jpeg")
# frames.append(frame)
scores.append(score)
