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Fix PPORecurrent training issue: tuned learning rate and added missing max_grad_norm #4

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Fix PPORecurrent training issue: tuned learning rate and added missing max_grad_norm #4

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1 change: 1 addition & 0 deletions rlopt/envs/gymlike.py
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Expand Up @@ -12,6 +12,7 @@
RewardSum,
StepCounter,
TransformedEnv,
VecNormV2
)
from torchrl.envs.libs.gym import GymEnv
from torchrl.envs.transforms import (
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3 changes: 2 additions & 1 deletion test/test_config.yaml
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Expand Up @@ -23,10 +23,11 @@ logger:

# Optim
optim:
lr: 3e-4
lr: 1e-4
weight_decay: 0.0
anneal_lr: True
device:
max_grad_norm: 0.5

# loss
loss:
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3 changes: 2 additions & 1 deletion test/test_ppo.py
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Expand Up @@ -6,7 +6,7 @@
import numpy as np
import torch
import torchrl.envs.libs.gym
from omegaconf import OmegaConf
from omegaconf import OmegaConf, DictConfig
from stable_baselines3.common.vec_env.base_vec_env import VecEnv
from tensordict import TensorDict
from torchrl.envs import EnvCreator, ParallelEnv, TransformedEnv
Expand Down Expand Up @@ -288,3 +288,4 @@ def test_training_improves_return_pporecurrent():

assert duration < 120.0
assert after > before + 0.01

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