Add Ensemble Discriminators

[Shehrozkashif]

📌 Background / Context

A single discriminator may have weaknesses in evaluating output quality. Using an ensemble of discriminators improves robustness and reduces variance in quality assessment.

🎯 Objectives

• Train multiple discriminators with diverse architectures
• Aggregate predictions to improve reliability
• Compare ensemble performance with single models

✅ Tasks

• Train multiple discriminators on the same dataset
• Implement voting or averaging for ensemble predictions
• Add configuration options for ensemble selection
• Benchmark ensemble vs. single discriminator performance