@Marvin I want to see Tensorflow/Keras output in my Prefect logs while I'm training a model, but it's not showing up when I run it in the cloud. It shows up when I run it interactively, though - how do I fix this?

To see TensorFlow/Keras logs in Prefect Cloud, you can follow these steps: 1. Configure Logging Levels: Ensure that your logging levels are set correctly. Prefect defaults to show

INFO

level logs and above, but TensorFlow/Keras might be emitting at a different level (e.g.,

DEBUG

).

shell
   prefect config set PREFECT_LOGGING_LEVEL=DEBUG

You can also set this in your environment:

shell
   export PREFECT_LOGGING_LEVEL=DEBUG

2. Use

get_run_logger

: Leverage Prefect's logging utility. Prefect provides a logger specific for flow runs that might help capture more context.

python
   from prefect import flow, task
   from prefect.logging import get_run_logger

   @task
   def train_model():
       logger = get_run_logger()
       # Your TensorFlow/Keras training logic here
       <http://logger.info|logger.info>("Training started.")
       # ...

   @flow
   def main_flow():
       train_model()

   if __name__ == "__main__":
       main_flow()

3. Verify Cloud Configuration: Make sure your Prefect Cloud configuration is correct. Check your API keys and URLs.

shell
   prefect config view

Ensure

PREFECT_API_URL

is set to

<https://api.prefect.cloud/api/>

and the

PREFECT_API_KEY

is valid. Sources: - Prefect 2.x Logging Guide - Prefect 2.x Troubleshooting - Prefect 3.0 Logging Configuration - Prefect 3.0 Troubleshooting Cloud If you still face issues, consider checking both Prefect's and TensorFlow/Keras' documentation for logging compatibility and make sure there are no conflicts.