From b7aa10e52bbada63cae89173d672551d6d1a1d9a Mon Sep 17 00:00:00 2001 From: Manan Goel Date: Sat, 23 Apr 2022 11:31:52 +0000 Subject: [PATCH] Added details on how the WandbLogger function works --- doc/doc_en/logging_en.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/doc/doc_en/logging_en.md b/doc/doc_en/logging_en.md index f57d8419..57f154f2 100644 --- a/doc/doc_en/logging_en.md +++ b/doc/doc_en/logging_en.md @@ -43,7 +43,12 @@ wandb: entity: my_team ``` -This will automatically log all the training and evaluation metrics to the W&B dashboard along with models at every model saving step and evaluation step are with the appropriate tags and metadata. +These config variables from the yaml file are used to instantiate the `WandbLogger` object with the project name, entity name (the logged in user by default), directory to store metadata (`./wandb` by default) and more. During the training process, the `log_metrics` function is called to log training and evaluation metrics at the training and evaluation steps respectively from the rank 0 process only. + +At every model saving step, the WandbLogger, logs the model using the `log_model` function along with relavant metadata and tags showing the epoch in which the model is saved, the model is best or not and so on. + +All the logging mentioned above is integrated into the `program.train` function and will generate dashboards like this - + ![W&B Dashboard](../imgs_en/wandb_metrics.png) ![W&B Models](../imgs_en/wandb_models.png) -- GitLab