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2 parents 6e1ac23 + f6351de commit 68d8cc7Copy full SHA for 68d8cc7
src/reward_preprocessing/interpret.py
@@ -290,7 +290,8 @@ def param_f():
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)
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# Now, we put the latent vector thru the generator to produce transition
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# tensors that we can get observations, actions, etc out of
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- opt_latent = np.squeeze(opt_latent)
+ opt_latent = np.squeeze(opt_latent, axis=(1, 2))
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+ # ^ squeeze out extraneous "height" and "width" dimensions
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opt_latent_th = th.from_numpy(opt_latent).to(th.device(device))
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opt_transitions = gan.generator(opt_latent_th)
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obs, acts, next_obs = tensor_to_transition(opt_transitions)
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