From 9691ddda459397096eb72b5e8cac2d4591ed107a Mon Sep 17 00:00:00 2001
From: Alexander Soare <alexander.soare159@gmail.com>
Date: Mon, 20 May 2024 07:43:45 +0100
Subject: [PATCH] Update the README to reflect WandB disabled by default

---
 README.md | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index a936ecfe..f7948f12 100644
--- a/README.md
+++ b/README.md
@@ -92,6 +92,8 @@ To use [Weights and Biases](https://docs.wandb.ai/quickstart) for experiment tra
 wandb login
 ```
 
+(note: you will also need to enable WandB in the configuration. See below.)
+
 ## Walkthrough
 
 ```
@@ -158,13 +160,14 @@ See `python lerobot/scripts/eval.py --help` for more instructions.
 
 Check out [example 3](./examples/3_train_policy.py) that illustrates how to start training a model.
 
-In general, you can use our training script to easily train any policy. To use wandb for logging training and evaluation curves, make sure you ran `wandb login`. Here is an example of training the ACT policy on trajectories collected by humans on the Aloha simulation environment for the insertion task:
+In general, you can use our training script to easily train any policy. To use wandb for logging training and evaluation curves, make sure you ran `wandb login`, and enable it in the configuration. Here is an example of training the ACT policy on trajectories collected by humans on the Aloha simulation environment for the insertion task:
 ```bash
 python lerobot/scripts/train.py \
     policy=act \
     env=aloha \
     env.task=AlohaInsertion-v0 \
-    dataset_repo_id=lerobot/aloha_sim_insertion_human
+    dataset_repo_id=lerobot/aloha_sim_insertion_human \
+    wandb.enable=true
 ```
 
 The experiment directory is automatically generated and will show up in yellow in your terminal. It looks like `outputs/train/2024-05-05/20-21-12_aloha_act_default`. You can manually specify an experiment directory by adding this argument to the `train.py` python command:
@@ -175,12 +178,6 @@ The experiment directory is automatically generated and will show up in yellow i
 A link to the wandb logs for the run will also show up in yellow in your terminal. Here is an example of logs from wandb:
 ![](media/wandb.png)
 
-You can deactivate wandb by adding these arguments to the `train.py` python command:
-```bash
-    wandb.disable_artifact=true \
-    wandb.enable=false
-```
-
 Note: For efficiency, during training every checkpoint is evaluated on a low number of episodes. After training, you may want to re-evaluate your best checkpoints on more episodes or change the evaluation settings. See `python lerobot/scripts/eval.py --help` for more instructions.