getCurrentState

Serializes complete neural network state for persistence and recovery.

Captures all learned parameters, training statistics, and performance metrics in a format suitable for storage and later restoration.

Serialized Components:

• Neural network weights and biases

• Training progress counters

• Performance history and metrics

• Model configuration metadata

Use Cases:

• Application shutdown/restart continuity

• Model checkpointing during training

• Performance analysis and debugging

• State transfer between instances

Thread Safety: Uses mutex to ensure consistent state capture Performance: Minimal overhead with efficient binary serialization

See also