Module qml 

Quantum Machine Learning (QML) module.

This module provides comprehensive quantum machine learning algorithms with hardware-aware optimization, adaptive training strategies, and support for various quantum computing architectures.

Re-exports

pub use benchmarks::benchmark_gradient_methods;

pub use benchmarks::benchmark_optimizers;

pub use benchmarks::benchmark_quantum_ml_algorithms;

pub use benchmarks::run_comprehensive_benchmarks;

pub use circuit::HardwareOptimizations;

pub use circuit::ParameterizedQuantumCircuit;

pub use config::GradientMethod;

pub use config::HardwareArchitecture;

pub use config::OptimizerType;

pub use config::QMLAlgorithmType;

pub use config::QMLConfig;

pub use trainer::CompilationStats;

pub use trainer::HardwareAwareCompiler;

pub use trainer::HardwareMetrics;

pub use trainer::OptimizerState;

pub use trainer::QuantumMLTrainer;

pub use trainer::TrainingHistory;

pub use trainer::TrainingResult;

Modules

benchmarks

Benchmarking functions for quantum machine learning algorithms.

circuit

Parameterized quantum circuits for machine learning applications.

config

Configuration structures and enums for quantum machine learning algorithms.

trainer

Quantum machine learning trainer implementation.

Functions

create_default_config

Create a default configuration for a specific algorithm

create_hardware_config

Create a configuration optimized for specific hardware

get_supported_algorithms

Get supported QML algorithms

get_supported_architectures

Get supported hardware architectures

get_supported_gradient_methods

Get supported gradient methods

get_supported_optimizers

Get supported optimizers

initialize

Initialize the QML subsystem

is_hardware_optimization_available

Check if hardware-aware optimization is available

validate_config

Validate QML configuration