How to visualize an attention mechanism in a classification task

Question

Can you tell me How to visualize an attention mechanism in a classification task?

Answer 1

To visualize an attention mechanism in a classification task, extract attention weights and overlay them on input features or images to highlight important regions contributing to the model’s decision.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Implements Self-Attention Mechanism with Query, Key, and Value layers.
• Extracts Attention Weights using the return_attention_scores=True flag.
• Uses Matplotlib Heatmap to visualize the attention distribution.
• Shows Which Features are Important for model decision-making.

Hence, visualizing attention in a classification task allows interpretability by highlighting key input features that influence the model’s predictions.