Instructions to use replicate/flash-mla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/flash-mla with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("replicate/flash-mla") - Notebooks
- Google Colab
- Kaggle
| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| struct Flash_fwd_mla_params { | |
| using index_t = int64_t; | |
| int b, seqlen_q, d, d_v; | |
| int h, h_h_k_ratio, ngroups; | |
| bool is_causal; | |
| float scale_softmax, scale_softmax_log2; | |
| int *__restrict__ cu_seqlens_k; | |
| void *__restrict__ q_ptr; | |
| void *__restrict__ k_ptr; | |
| void *__restrict__ v_ptr; | |
| void *__restrict__ o_ptr; | |
| void *__restrict__ softmax_lse_ptr; | |
| index_t q_batch_stride; | |
| index_t k_batch_stride; | |
| index_t v_batch_stride; | |
| index_t o_batch_stride; | |
| index_t q_row_stride; | |
| index_t k_row_stride; | |
| index_t v_row_stride; | |
| index_t o_row_stride; | |
| index_t q_head_stride; | |
| index_t k_head_stride; | |
| index_t v_head_stride; | |
| index_t o_head_stride; | |
| int *__restrict__ block_table; | |
| index_t block_table_batch_stride; | |
| int page_block_size; | |
| int *__restrict__ tile_scheduler_metadata_ptr; | |
| int num_sm_parts; | |
| int *__restrict__ num_splits_ptr; | |
| void *__restrict__ softmax_lseaccum_ptr; | |
| void *__restrict__ oaccum_ptr; | |
| }; | |
| static constexpr int TileSchedulerMetaDataSize = 8; | |
| // [begin_idx, begin_seqlen, end_idx, end_seqlen, begin_n_split_idx, _, _, _] | |
| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| template<typename T, int Headdim> | |
| void run_mha_fwd_splitkv_mla(Flash_fwd_mla_params ¶ms, cudaStream_t stream); | |
| struct Mla_metadata_params { | |
| int *__restrict__ seqlens_k_ptr; | |
| int *__restrict__ tile_scheduler_metadata_ptr; | |
| int *__restrict__ num_splits_ptr; | |
| int batch_size; | |
| int block_size_n; | |
| int fixed_overhead_num_blocks; | |
| int num_sm_parts; | |
| }; | |
| void get_mla_metadata_func(Mla_metadata_params ¶ms, cudaStream_t stream); | |