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# params for quick debug on the CPU, should be 0.8+ score | ||
env_id: "XLand-MiniGrid-R1-9x9" | ||
benchmark_id: "trivial-1m" | ||
rnn_hidden_dim: 32 | ||
head_hidden_dim: 16 | ||
num_envs: 256 | ||
num_steps_per_env: 736 | ||
num_steps_per_update: 16 | ||
total_timesteps: 2_000_000 | ||
eval_num_envs: 64 | ||
eval_num_episodes: 3 |
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# params for quick debug on the CPU, should be 0.8+ score | ||
env_id: "MiniGrid-Empty-6x6" | ||
rnn_hidden_dim: 16 | ||
head_hidden_dim: 16 | ||
num_envs: 64 | ||
total_timesteps: 100000 |
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# params used in the paper for meta-RL experiments. Overwrite default benchmark_id if needed. | ||
env_id: "XLand-MiniGrid-R4-13x13" | ||
benchmark_id: "high-1m" | ||
total_timesteps: 10_000_000_000 | ||
num_envs: 16384 | ||
num_steps_per_env: 12800 | ||
num_steps_per_update: 256 | ||
update_epochs: 1 | ||
num_minibatches: 32 | ||
eval_num_envs: 16384 | ||
eval_num_episodes: 25 | ||
train_seed: 5 |
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# params used in the paper for meta-RL with RGB observations experiments. Overwrite default benchmark_id if needed. | ||
env_id: "XLand-MiniGrid-R1-13x13" | ||
benchmark_id: "high-1m" | ||
total_timesteps: 500_000_000 | ||
num_envs: 1024 | ||
num_steps_per_env: 12800 | ||
num_steps_per_update: 128 | ||
update_epochs: 1 | ||
num_minibatches: 32 | ||
eval_num_envs: 8192 | ||
eval_num_episodes: 25 | ||
img_obs: True | ||
lr: 0.0001 | ||
train_seed: 5 |
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# params used in the paper for trillion transitions experiment. | ||
# params optimized for 8xA100 GPU node | ||
env_id: "XLand-MiniGrid-R4-13x13" | ||
benchmark_id: "high-1m" | ||
total_timesteps: 1_000_000_000_000 | ||
num_envs: 131072 | ||
num_steps_per_env: 12800 | ||
num_steps_per_update: 256 | ||
update_epochs: 1 | ||
num_minibatches: 32 | ||
eval_num_envs: 16384 | ||
eval_num_episodes: 25 | ||
train_seed: 5 |
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# params used in the paper for single-RL experiments. | ||
env_id: "XLand-MiniGrid-R4-13x13" | ||
benchmark_id: "trivial-1m" | ||
ruleset_id: 0 | ||
total_timesteps: 1_000_000_000 | ||
num_envs: 16384 | ||
num_steps: 256 | ||
update_epochs: 1 | ||
num_minibatches: 8 | ||
eval_episodes: 512 | ||
train_seed: 5 |