FlagAttention is a library implementing memory-efficient attention operators in the Triton language. It provides optimized implementations of flash attention, piecewise attention, paged attention, and gated delta rule operations, designed for use in large language model training and inference. The library features modular architecture with separate implementations for each attention variant, comprehensive testing, and example usage patterns. It leverages Triton for GPU-accelerated computations while maintaining compatibility with PyTorch's autograd system.