small updates for dm (Denys88#235)

* a lot of small changes * two hot almost works * added deepmind * readme * small imporvements * fixed merge * fixed stand * fxied --------- Co-authored-by: Noname <nepalimsa@>
kelvin34501 · Apr 23, 2023 · c0caa2e · c0caa2e
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diff --git a/README.md b/README.md
@@ -292,6 +292,8 @@ Additional environment supported properties and functions
 * Added Deepmind Control PPO benchmark.
 * Added a few more experimental ways to train value prediction (OneHot, TwoHot encoding and crossentropy loss instead of L2).
 * New methods didn't. It is impossible to turn it on from the yaml files. Once we find an env which trains better it will be added to the config.
+* Added shaped reward graph to the tensorboard. 
+
 
 1.6.0
 

diff --git a/docs/DEEPMIND_ENVPOOL.md b/docs/DEEPMIND_ENVPOOL.md
@@ -13,7 +13,7 @@ poetry run python runner.py --train --file rl_games/configs/dm_control/humanoid_
 ## Results:
 
 * No tuning. I just run it on a couple of envs.
-* I used 4000 epochs which is ~32M steps for almost all envs except HumanoidRun. But a few millions of stepsa was enough for the most of the envs.
+* I used 4000 epochs which is ~32M steps for almost all envs except HumanoidRun. But a few millions of steps was enough for the most of the envs.
 * Deepmind used a pretty strange reward and training rules. A simple reward transformation: log(reward + 1) achieves best scores faster.
 
 | Env           | Rewards       |