README.md

---
library_name: kernels
license: bsd-3-clause
---

# flash-sparse-attention

Flash Sparse Attention Triton kernels — dense, sparse, and gated attention
with forward, backward, and decode paths.

## Usage

```python
from kernels import get_kernel

fsa = get_kernel("JingzeShi/flash-sparse-attention", version=1)

# Dense forward
out = fsa.flash_dense_attn_func(q, k, v, is_causal=True)

# Decode with KV cache
out = fsa.flash_dense_attn_with_kvcache_func(q, k, v)

# Sparse attention
out = fsa.flash_sparse_attn_func(q, k, v, is_causal=True, softmax_threshold=0.01)

# Gated attention
out = fsa.flash_gated_attn_func(q, k, v, alpha, delta, is_causal=True)
```

## Available functions

- `flash_dense_attn_func`
- `flash_dense_attn_with_kvcache_func`
- `flash_dense_attn_varlen_func`
- `flash_dense_attn_varlen_with_kvcache_func`
- `flash_sparse_attn_func`
- `flash_sparse_attn_with_kvcache_func`
- `flash_sparse_attn_varlen_func`
- `flash_sparse_attn_varlen_with_kvcache_func`
- `flash_gated_attn_func`
- `flash_gated_attn_with_kvcache_func`
- `flash_gated_attn_varlen_func`
- `flash_gated_attn_varlen_with_kvcache_func`

## Source

Originally from [HKUSTDial/flash-sparse-attention](https://github.com/HKUSTDial/flash-sparse-attention).