| import torch |
| import triton |
| import triton.language as tl |
|
|
| from fla.ops.utils import prepare_chunk_indices |
|
|
|
|
| @triton.heuristics({ |
| 'IS_VARLEN': lambda args: args['offsets'] is not None, |
| }) |
| @triton.jit(do_not_specialize=['T']) |
| def parallel_path_fwd_kernel_prepare_k_cache( |
| k, k_new, w1, w2, |
| offsets, indices, |
| T, |
| H: tl.constexpr, |
| K: tl.constexpr, |
| BT: tl.constexpr, BK: tl.constexpr, |
| IS_VARLEN: tl.constexpr, |
| ): |
| i_t, i_bh = tl.program_id(0), tl.program_id(1) |
| i_b, i_h = i_bh // H, i_bh % H |
|
|
| if IS_VARLEN: |
| i_n, i_t = tl.load(indices + i_t * 2).to(tl.int32), tl.load(indices + i_t * 2 + 1).to(tl.int32) |
| bos, eos = tl.load(offsets + i_n).to(tl.int32), tl.load(offsets + i_n + 1).to(tl.int32) |
| T = eos - bos |
| else: |
| i_n = i_b |
| bos, eos = i_n * T, i_n * T + T |
|
|
| k += (bos * H + i_h) * K |
| k_new += (bos * H + i_h) * K |
| w1 += (bos * H + i_h) * K |
| w2 += (bos * H + i_h) * K |
| |
| p_k = tl.make_block_ptr(k, (T, K), (H*K, 1), (i_t * BT, 0), (BT, BK), (1, 0)) |
| b_k = tl.zeros([BT, BK], dtype=tl.float32) |
| b_k += tl.load(p_k, boundary_check=(0, 1)) |
| for k_block_idx in range(i_t + 1, tl.cdiv(T, BT)): |
| p_w1 = tl.make_block_ptr(w1, (T, K), (H*K, 1), (k_block_idx * BT, 0), (BT, BK), (1, 0)) |
| p_w2 = tl.make_block_ptr(w2, (T, K), (H*K, 1), (k_block_idx * BT, 0), (BT, BK), (1, 0)) |
| b_w1 = tl.load(p_w1, boundary_check=(0, 1)) |
| b_w2 = tl.load(p_w2, boundary_check=(0, 1)) |
| b_A = tl.dot(b_k.to(b_w2.dtype), tl.trans(b_w2)) |
| b_k = b_k - tl.dot(b_A.to(b_w1.dtype), b_w1) |
|
|
| p_k_new = tl.make_block_ptr(k_new, (T, K), (H*K, 1), (i_t * BT, 0), (BT, BK), (1, 0)) |
| tl.store(p_k_new, b_k.to(p_k_new.dtype.element_ty), boundary_check=(0, 1)) |
|
|
|
|
| def prepare_k_cache_fn(k, w1, w2, cu_seqlens, BS, use_cache=False): |
| if not use_cache: |
| return None |
| else: |
| B, T, H, K = k.shape |
| k_new = torch.empty_like(k) |
| indices = prepare_chunk_indices(cu_seqlens, BS) if cu_seqlens is not None else None |
| NT = triton.cdiv(T, BS) if cu_seqlens is None else len(indices) |
| grid = (NT, B * H) |
| parallel_path_fwd_kernel_prepare_k_cache[grid]( |
| k=k, |
| k_new=k_new, |
| w1=w1, |
| w2=w2, |
| offsets=cu_seqlens, |
| indices=indices, |
| H=H, |
| T=T, |
| K=K, |
| BT=BS, |
| BK=triton.next_power_of_2(K), |
| ) |
| return k_new |
|
|
