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You want to combine a GRU layer with an attention mechanism for text classification. Which of the following best describes how to integrate attention with GRU outputs?

hard📝 Application Q9 of 15
NLP - Sequence Models for NLP
You want to combine a GRU layer with an attention mechanism for text classification. Which of the following best describes how to integrate attention with GRU outputs?
AUse attention only on the initial input embeddings, ignoring GRU outputs
BApply attention weights on GRU outputs across all time steps before classification
CReplace GRU gates with attention weights
DApply attention on the hidden state of the last GRU layer only
Step-by-Step Solution
Solution:

  1. Step 1: Understand attention in sequence models

    Attention assigns importance to each time step's output from GRU.

  2. Step 2: Apply attention on all GRU outputs

    Weighted sum of outputs improves focus on relevant words before classification.

  3. Final Answer:

    Apply attention weights on GRU outputs across all time steps before classification -> Option B

  4. Quick Check:

    Attention weights on all outputs = better context [OK]
Quick Trick: Attention weights highlight important GRU outputs over time [OK]
Common Mistakes:
MISTAKES
  • Replacing GRU gates with attention
  • Ignoring GRU outputs in attention
  • Applying attention only on last hidden state

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