Module memory 

Memory optimization utilities for large factor graphs.

This module provides memory-efficient representations and operations for probabilistic graphical models, including:

• Memory pooling for factor allocation
• Sparse factor representation for factors with many zeros
• Lazy evaluation for factor operations
• Memory-mapped factors for very large models

Structs

BlockSparseFactor

Block-sparse factor for factors with block structure.

CompressedFactor

Compressed factor using quantization.

FactorPool

Memory pool for factor value arrays.

LazyFactor

Lazy factor that defers computation until needed.

MemoryEstimate

Memory usage estimate.

PoolStats

Statistics for memory pool usage.

SparseFactor

Sparse factor representation using coordinate format.

StreamingFactorGraph

Memory-efficient factor graph for very large models.

Functions

estimate_memory_usage

Estimate memory usage for a factor graph.