oxirs-vec 0.2.4

Vector index abstractions for semantic similarity and AI-augmented querying
Documentation 
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//! Neural Architecture Search (NAS) for optimal embedding architectures
//!
//! This module implements state-of-the-art Neural Architecture Search techniques
//! to automatically discover optimal neural network architectures for embeddings.
//! It supports multiple search strategies including evolutionary algorithms,
//! reinforcement learning, and Bayesian optimization.

pub mod config;
pub mod types;
pub mod architecture;
pub mod search_strategy;
pub mod evaluator;
pub mod monitoring;
pub mod dataset;
pub mod history;
pub mod engine;

// Re-export main types for convenience
pub use config::*;
pub use types::*;
pub use architecture::*;
pub use search_strategy::*;
pub use evaluator::*;
pub use monitoring::*;
pub use dataset::*;
pub use history::*;
pub use engine::NeuralArchitectureSearch;

use anyhow::Result;

/// Initialize neural architecture search system
pub fn initialize_nas() -> Result<()> {
    // Initialize any global NAS components
    Ok(())
}

/// Check if NAS is available
pub fn is_nas_available() -> bool {
    // Check if required dependencies are available
    true
}