//! Complete Generative Models Example (Placeholder)
//!
//! This example demonstrates the implementation of various generative models
//! including Variational Autoencoders (VAE), Generative Adversarial Networks (GAN),
//! and conditional generation techniques.

use scirs2_neural::error::Result;

#[allow(dead_code)]
fn main() -> Result<()> {
    println!("=== Generative Models Complete Example ===");
    println!("Note: This example is not yet implemented in the minimal version.");
    println!("This is a placeholder for future generative models functionality.");

    println!("\nPlanned features:");
    println!("- Variational Autoencoders (VAE)");
    println!("- Generative Adversarial Networks (GAN)");
    println!("- Conditional generation");
    println!("- Style transfer models");

    println!("\nTo implement these features, the following modules would be needed:");
    println!("- Advanced layer types (BatchNorm, AdaptiveMaxPool2D, etc.)");
    println!("- Generative loss functions");
    println!("- Advanced optimizers");
    println!("- Data augmentation utilities");

    Ok(())
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_example_runs() {
        assert!(main().is_ok());
    }
}
