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![]() The DDPG/TD3 algorithms currently do not have a PyTorch implementation. This PR adds PyTorch support for DDPG/TD3 to RLlib. This PR: - Depends on the re-factor PR for DDPG (Functional Algorithm API). - Adds learning regression tests for the PyTorch version of DDPG and a DDPG (torch) - Updates the documentation to reflect that DDPG and TD3 now support PyTorch. * Learning Pendulum-v0 on torch version (same config as tf). Wall time a little slower (~20% than tf). * Fix GPU target model problem. |
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.. | ||
tests | ||
__init__.py | ||
epsilon_greedy.py | ||
exploration.py | ||
gaussian_noise.py | ||
ornstein_uhlenbeck_noise.py | ||
parameter_noise.py | ||
per_worker_epsilon_greedy.py | ||
per_worker_gaussian_noise.py | ||
per_worker_ornstein_uhlenbeck_noise.py | ||
random.py | ||
soft_q.py | ||
stochastic_sampling.py |