yusukeurakami / dreamer-pytorch

pytorch-implementation of Dreamer (Model-based Image RL Algorithm)
MIT License
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Does the walker run reproduce correctly? #4

Open letusfly85 opened 4 years ago

letusfly85 commented 4 years ago

Hi, thank you for the cool repository!

I tried several tasks walker walk, cheetah run. They seem to work fine.

But when I run walker run, the episode_reward cannot achieve around 700. Is there any problem...? πŸ€”

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The original paper seems to say walker run will achieve around 700 with 1M steps, saying on the following page 7, Figure7.

https://arxiv.org/pdf/1912.01603.pdf

Thank you.

yusukeurakami commented 2 years ago

I know it is too late to comment on this issue but could you tell me the hyper parameters you tried this experiment?

coderlemon17 commented 1 year ago

@yusukeurakami Hi, I also find that the results for walker-run are weird, I ran the experiment with 5 different seeds, and here's what I got: image

And the hyperparameters I use are:

Hyperparameters ``` action_noise: 0.3 action_repeat: 2 actor_lr: 8.0e-05 adam_epsilon: 1.0e-07 algo: dreamer batch_size: 50 belief_size: 200 bit_depth: 5 candidates: 1000 checkpoint_interval: 50 chunk_size: 50 cnn_activation_function: relu collect_interval: 100 comment: '' config: dm_control/dreamer/walker-run.yaml dense_activation_function: elu device: cuda:3 embedding_size: 1024 env: walker-run episodes: 1000 exp_ckpt: '' experience_size: 1000000 free_nats: 3 gamma: 0.99 global_kl_beta: 0.0 grad_clip_norm: 100.0 hidden_size: 200 id: dreamer lambda_: 0.95 max_episode_length: 1000 model_ckpt: '' model_lr: 0.001 model_lr_schedule: 0 optimisation_iters: 10 overshooting_distance: 50 overshooting_kl_beta: 0.0 overshooting_reward_scale: 0.0 planning_horizon: 15 render: false save_experience_buffer: false seed: 0 seed_episodes: 5 state_size: 30 symbolic_env: false test: false test_episodes: 10 test_interval: 10 top_candidates: 100 torch_deterministic: true value_lr: 8.0e-05 worldmodel_LogProbLoss: false ```
yingchengyang commented 1 year ago

The same question. Hoping for your reply. Thanks.