How to Disable All TensorFlow Warnings in Python

Discover a quick and effective way to `silence TensorFlow warnings` using a simple code snippet, ensuring a smoother development experience.
---

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How to disable all tensorflow warnings?

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Disable All TensorFlow Warnings in Python

When working with deep learning models in TensorFlow, it’s common to encounter warnings especially when you're iterating through models in a loop. These warnings can clutter your console, making it challenging to focus on more critical outputs of your program. If you've ever found yourself wondering how to navigate through these repetitive alerts, you're not alone.

Understanding the Warning

In TensorFlow, you may run across messages that look like this:

[[See Video to Reveal this Text or Code Snippet]]

These warnings typically indicate issues such as:

Passing tensors with varying shapes, leading to unnecessary retracing and performance overhead.

Using Python objects instead of tensors, which can complicate the model's execution flow.

To solve this, you can either adjust your code to prevent the warnings or, if you prefer a cleaner output, disable them entirely.

Method to Disable TensorFlow Warnings

If your goal is to silence these warnings entirely, TensorFlow provides a straightforward command you can use in your Python scripts. This command sets the logging verbosity level, which controls what messages are displayed during program execution.

Here's How To Do It

To disable TensorFlow warnings, apply the following code snippet at the start of your script or notebook:

[[See Video to Reveal this Text or Code Snippet]]

Steps to Implement:

Import TensorFlow: Ensure you import the TensorFlow library in your script.

Set Verbosity Level: Add the command to change the logging level to ERROR, which will prevent warnings and info messages from appearing.

Run Your Script: Execute your program as usual. You should no longer see the TensorFlow warnings flooding your console.

Conclusion

Silencing TensorFlow warnings can enhance your programming experience, allowing you to focus on critical parts of your project without distractions. By implementing the simple command above, you steer clear of the verbose outputs that can arise when working with multiple models. However, do keep in mind that while disabling warnings can simplify your console output, it might be beneficial to address the underlying issues in your code for a more efficient and optimized workflow. Happy coding!