For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /get-started.md).
Mojo function
naive_grouped_matmul
def naive_grouped_matmul[*, transpose_b: Bool = True, elementwise_lambda_fn: Optional[def[dtype: DType, width: SIMDLength, *, alignment: Int = Int(1)](IndexList[Int(2)], SIMD[dtype, width]) capturing thin -> None] = None, a_plane_splits: IndexList[Int(2)] = Index[Int, Int](Int(0), Int(0))](c: TileTensor[Engine=c.Engine, linear_idx_type=c.linear_idx_type], a: TileTensor[Engine=a.Engine, linear_idx_type=a.linear_idx_type], b: TileTensor[Engine=b.Engine, linear_idx_type=b.linear_idx_type], a_offsets: TileTensor[.uint32, Engine=a_offsets.Engine, linear_idx_type=a_offsets.linear_idx_type], expert_ids: TileTensor[.int32, Engine=expert_ids.Engine, linear_idx_type=expert_ids.linear_idx_type], max_num_tokens_per_expert: Int, num_active_experts: Int, ctx: DeviceContext)
TileTensor primary implementation of naive_grouped_matmul.