For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /max/get-started.md).
Mojo function
sparse_indexer_decode_topk
def sparse_indexer_decode_topk[num_index_heads: Int, block_size: Int](seq_lens: TileTensor[DType.uint32, address_space=seq_lens.address_space, linear_idx_type=seq_lens.linear_idx_type, element_size=seq_lens.element_size], score: TileTensor[DType.float32, address_space=score.address_space, linear_idx_type=score.linear_idx_type, element_size=score.element_size], out_idxs: TileTensor[DType.int32, address_space=out_idxs.address_space, linear_idx_type=out_idxs.linear_idx_type, element_size=out_idxs.element_size], batch: Int, max_num_blocks: Int, topk: Int, ctx: DeviceContext)
Launch the decode top-k selection kernel from score into out_idxs.
See sparse_indexer_decode for the argument contract. Exposed separately so
tests can drive scoring and selection independently.
Was this page helpful?
Thank you! We'll create more content like this.
Thank you for helping us improve!