File size: 6,793 Bytes
b66f552 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 | import torch
import triton
import triton.language as tl
from fla.ops.utils import prepare_chunk_indices
@triton.heuristics({
'USE_GATE': lambda args: args['g_cumsum'] is not None,
'IS_VARLEN': lambda args: args['cu_seqlens'] is not None,
})
@triton.jit(do_not_specialize=['T'])
def parallel_path_fwd_kernel(
q,
k,
v,
o,
o_new,
g_cumsum,
w1,
w2,
scale,
L,
L_new,
M,
cu_seqlens,
indices,
T,
G: tl.constexpr,
HQ: tl.constexpr,
H: tl.constexpr,
K: tl.constexpr,
V: tl.constexpr,
BT: tl.constexpr,
BS: tl.constexpr,
BK: tl.constexpr,
BV: tl.constexpr,
USE_GATE: tl.constexpr,
IS_VARLEN: tl.constexpr,
):
i_t, i_bh = tl.program_id(0), tl.program_id(1)
i_b, i_hq = i_bh // HQ, i_bh % HQ
i_h = i_hq // G
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(cu_seqlens + i_n).to(tl.int32), tl.load(cu_seqlens + i_n + 1).to(tl.int32)
T = eos - bos
else:
i_n = i_b
bos, eos = i_n * T, i_n * T + T
p_q = tl.make_block_ptr(q + (bos * HQ + i_hq) * K, (T, K), (HQ*K, 1), (i_t * BT, 0), (BT, BK), (1, 0))
b_q = tl.zeros([BT, BK], dtype=tl.float32)
b_q += tl.load(p_q, boundary_check=(0, 1))
sm_scale = scale * 1.44269504
b_o = tl.zeros([BT, BV], dtype=tl.float32)
p_o = tl.make_block_ptr(o + (bos * HQ + i_hq) * V, (T, V), (HQ*V, 1), (i_t * BT, 0), (BT, BV), (1, 0))
b_o += tl.load(p_o, boundary_check=(0, 1))
p_L = tl.make_block_ptr(L + bos * HQ + i_hq, (T, ), (HQ, ), (i_t * BT, ), (BT, ), (0,))
p_M = tl.make_block_ptr(M + bos * HQ + i_hq, (T, ), (HQ, ), (i_t * BT, ), (BT, ), (0,))
b_l = tl.load(p_L, boundary_check=(0,))
b_m = tl.load(p_M, boundary_check=(0,))
if USE_GATE:
p_g_cumsum_q = tl.make_block_ptr(g_cumsum + bos * HQ + i_hq, (T, ), (HQ, ), (i_t * BT, ), (BT, ), (0,))
b_g_cumsum_q = tl.load(p_g_cumsum_q, boundary_check=(0,))
else:
b_g_cumsum_q = None
for offset in range((i_t + 1) * BT - 2 * BS, i_t*BT-BS, -BS):
p_k = tl.make_block_ptr(k + (bos * H + i_h) * K, (K, T), (1, K*H), (0, offset), (BK, BS), (0, 1)) # GQA when H!=HQ
p_v = tl.make_block_ptr(v + (bos * H + i_h) * V, (T, V), (V*H, 1), (offset, 0), (BS, BV), (1, 0)) # GQA when H!=HQ
p_w1 = tl.make_block_ptr(w1 + (bos * H + i_h) * K, (K, T), (1, K*H), (0, offset), (BK, BS), (0, 1))
p_w2 = tl.make_block_ptr(w2 + (bos * H + i_h) * K, (T, K), (K*H, 1), (offset, 0), (BS, BK), (1, 0))
# [BK, BS]
b_k = tl.load(p_k, boundary_check=(0, 1))
# [BS, BV]
b_v = tl.load(p_v, boundary_check=(0, 1))
# [BK, BK]
b_w1 = tl.load(p_w1, boundary_check=(0, 1))
b_w2 = tl.load(p_w2, boundary_check=(0, 1))
# [BT, BS]
m_s = i_t * BT + tl.arange(0, BT) >= (offset + BS)
b_s = tl.dot(b_q.to(b_k.dtype), b_k)
if USE_GATE:
p_g_cumsum_k = tl.make_block_ptr(g_cumsum + (bos * HQ + i_hq), (T, ), (HQ, ), (offset, ), (BS, ), (0,))
b_g_cumsum_k = tl.load(p_g_cumsum_k, boundary_check=(0,))
b_s = b_s + b_g_cumsum_q[:, None] - b_g_cumsum_k[None, :]
b_s = tl.where(m_s[:, None], b_s * sm_scale, float("-inf"))
b_m_new = tl.maximum(b_m, tl.max(b_s, 1))
alpha = tl.math.exp2(b_m - b_m_new)
b_s = tl.math.exp2(b_s - b_m_new[:, None])
b_o *= alpha[:, None]
b_l = b_l * alpha + tl.sum(b_s, 1)
b_m = b_m_new
b_o += tl.dot(b_s.to(b_v.dtype), b_v)
b_s2 = tl.dot(b_q.to(b_w1.dtype), b_w1)
b_s2 = tl.where(m_s[:, None], b_s2, 0)
b_q -= tl.dot(b_s2.to(b_w2.dtype), b_w2)
tl.debug_barrier()
for offset in range(i_t * BT - BS, -BS, -BS):
p_k = tl.make_block_ptr(k + (bos * H + i_h) * K, (K, T), (1, K*H), (0, offset), (BK, BS), (0, 1)) # GQA when H!=HQ
p_v = tl.make_block_ptr(v + (bos * H + i_h) * V, (T, V), (V*H, 1), (offset, 0), (BS, BV), (1, 0)) # GQA when H!=HQ
p_w1 = tl.make_block_ptr(w1 + (bos * H + i_h) * K, (K, T), (1, K*H), (0, offset), (BK, BS), (0, 1))
p_w2 = tl.make_block_ptr(w2 + (bos * H + i_h) * K, (T, K), (K*H, 1), (offset, 0), (BS, BK), (1, 0))
# [BK, BS]
b_k = tl.load(p_k, boundary_check=(0, 1))
# [BS, BV]
b_v = tl.load(p_v, boundary_check=(0, 1))
b_w1 = tl.load(p_w1, boundary_check=(0, 1))
b_w2 = tl.load(p_w2, boundary_check=(0, 1))
# [BT, BS]
b_s = tl.dot(b_q.to(b_k.dtype), b_k)
if USE_GATE:
p_g_cumsum_k = tl.make_block_ptr(g_cumsum + (bos * HQ + i_hq), (T, ), (HQ, ), (offset, ), (BS, ), (0,))
b_g_cumsum_k = tl.load(p_g_cumsum_k, boundary_check=(0,))
b_s = b_s + b_g_cumsum_q[:, None] - b_g_cumsum_k[None, :]
b_s = b_s * sm_scale
b_m_new = tl.maximum(b_m, tl.max(b_s, 1))
alpha = tl.math.exp2(b_m - b_m_new)
b_s = tl.math.exp2(b_s - b_m_new[:, None])
b_o *= alpha[:, None]
b_l = b_l * alpha + tl.sum(b_s, 1)
b_m = b_m_new
b_o += tl.dot(b_s.to(b_v.dtype), b_v)
b_s2 = tl.dot(b_q.to(b_w1.dtype), b_w1)
b_q -= tl.dot(b_s2.to(b_w2.dtype), b_w2)
b_o = b_o / b_l[:, None]
p_o_new = tl.make_block_ptr(o_new + (bos * HQ + i_hq) * V, (T, V), (HQ*V, 1), (i_t*BT, 0), (BT, BV), (1, 0))
tl.store(p_o_new, b_o.to(p_o_new.dtype.element_ty), boundary_check=(0, 1))
b_l = tl.math.log2(b_l) + b_m
p_L_new = tl.make_block_ptr(L_new + (bos * HQ + i_hq), (T, ), (HQ, ), (i_t * BT, ), (BT, ), (0,))
tl.store(p_L_new, b_l.to(p_L_new.dtype.element_ty), boundary_check=(0,))
def parallel_path_fwd_fn(
q,
k,
v,
o,
g_cumsum,
w1,
w2,
scale,
L,
M,
cu_seqlens,
BT,
BS,
):
B, T, HQ, K = q.shape
V = v.shape[-1]
H = k.shape[-2]
G = HQ // H
indices = prepare_chunk_indices(cu_seqlens, BT) if cu_seqlens is not None else None
NT = triton.cdiv(T, BT) if cu_seqlens is None else len(indices)
grid = (NT, B * HQ)
o_new = torch.empty_like(o, dtype=v.dtype)
L_new = torch.empty_like(L)
parallel_path_fwd_kernel[grid](
q=q,
k=k,
v=v,
o=o,
o_new=o_new,
w1=w1,
w2=w2,
g_cumsum=g_cumsum,
scale=scale,
cu_seqlens=cu_seqlens,
indices=indices,
L=L,
L_new=L_new,
M=M,
T=T,
K=K,
V=V,
BK=triton.next_power_of_2(K),
BV=triton.next_power_of_2(V),
G=G,
HQ=HQ,
H=H,
BS=BS,
BT=BT,
num_warps=8 if (BT == 128 and K == 128) else 4,
)
return o_new, L_new
|