CS5720 - Week 9
Slide 177 of 180

Debugging Deep Learning Models

Essential Debugging Tools

  • 📊
    TensorBoard & Visualization
    Monitor training in real-time with interactive graphs
  • 📈
    Gradient Analysis
    Check for vanishing/exploding gradients
  • 🔍
    Model Hooks & Callbacks
    Inspect intermediate layer outputs
  • Performance Profiling
    Identify bottlenecks and memory issues

Common Issues & Solutions

  • 🚫
    Model Not Learning
    Loss stuck or increasing during training
  • 📉
    Overfitting
    Great training performance, poor validation
  • 💥
    NaN/Inf Values
    Numerical instabilities during training
  • 💾
    Out of Memory
    GPU/RAM exhaustion problems

Systematic Debugging Workflow

1
Reproduce Issue
2
Simplify Problem
3
Inspect & Analyze
4
Fix & Validate
Prepared by Dr. Gorkem Kar