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I'm interested in training an agent from the images while also recording the corresponding RAM states for later analysis. Previously, I have been using env._get_ram() for this purpose, but it seems that the method is no longer available. Is there a way to do this with the new API?
import gym
env = gym.make('ALE/Breakout-v5',
obs_type='rgb', # ram | rgb | grayscale <-- I would like both ram and grayscale
frameskip=5, # frame skip
mode=0, # game mode, see Machado et al. 2018
difficulty=0, # game difficulty, see Machado et al. 2018
repeat_action_probability=0.25, # Sticky action probability
full_action_space=True, # Use all actions
render_mode=None # None | human | rgb_array
)
The text was updated successfully, but these errors were encountered:
You'll still be able to get the RAM buffer by calling,
ram=env.ale.getRAM()
# OR if you want something more efficient depending on your circumstancesram=np.empty((env.ale.getRAMSize(),), dtype=np.uint8)
env.ale.getRAM(ram)
I'm interested in training an agent from the images while also recording the corresponding RAM states for later analysis. Previously, I have been using
env._get_ram()
for this purpose, but it seems that the method is no longer available. Is there a way to do this with the new API?The text was updated successfully, but these errors were encountered: