forked from RWKV/rwkv.cpp
/
rwkv_operators_wkv_v5.inc
180 lines (155 loc) · 6.41 KB
/
rwkv_operators_wkv_v5.inc
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
// Ported from https://github.com/harrisonvanderbyl/RNN-Factory/blob/3b696b547cc9e25de04a077602c3fe1133d8984c/src/models/modules/cuda/cpuonly.cpp#L8
// Original code by Harrison Vanderbyl.
// TODO Fix 1. unaligned memory access on Linux with AVX2, 2. tiny-rwkv with AVX-512
/*#ifdef __AVX512F__
#include <immintrin.h>
#define SIMD_WIDTH 16
#define LOAD(x) _mm512_load_ps(x)
#define STORE(x, y) _mm512_store_ps(x, y)
#define SET1(x) _mm512_set1_ps(x)
#define MULTIPLY(x, y) _mm512_mul_ps(x, y)
#define MULTADD(x, y, z) _mm512_fmadd_ps(x, y, z)
#elif __AVX2__
#include <immintrin.h>
#define SIMD_WIDTH 8
#define LOAD(x) _mm256_load_ps(x)
#define STORE(x, y) _mm256_store_ps(x, y)
#define SET1(x) _mm256_set1_ps(x)
#define MULTIPLY(x, y) _mm256_mul_ps(x, y)
#define MULTADD(x, y, z) _mm256_fmadd_ps(x, y, z)
#elif defined(__ARM_NEON) || defined(__ARM_NEON__)
#include <arm_neon.h>
#define SIMD_WIDTH 4
#define LOAD(x) vld1q_f32(x)
#define STORE(x, y) vst1q_f32(x, y)
#define SET1(x) vdupq_n_f32(x)
#define MULTIPLY(x, y) vmulq_f32(x, y)
#define MULTADD(x, y, z) vmlaq_f32(z, x, y)
#else*/
#define SIMD_WIDTH 1
#define LOAD(x) *x
#define STORE(x, y) *x = y
#define SET1(x) x
#define MULTIPLY(x, y) x * y
#define MULTADD(x, y, z) x * y + z
//#endif
// Ported from https://github.com/harrisonvanderbyl/RNN-Factory/blob/3b696b547cc9e25de04a077602c3fe1133d8984c/src/models/modules/cuda/cpuonly.cpp#L57
// Original code by Harrison Vanderbyl.
static void rwkv_wkv_v5_impl(struct ggml_tensor * result, const struct ggml_tensor * src, int ith, int nth, void * userdata) {
const size_t T = result->ne[1];
const size_t C = result->ne[0];
const size_t H = result->src[1]->ne[2];
float * result_data = (float *) result->data;
memset(result_data, 0, T * C * sizeof(float));
float * k = (float *) result->src[1]->data;
float * v = (float *) result->src[2]->data;
float * r = (float *) result->src[3]->data;
float * time_f = (float *) result->src[4]->data;
float * time_decay = (float *) result->src[5]->data;
float * state = (float *) result->src[6]->data;
size_t t_stride = H * (C / H);
size_t h_stride = C / H;
size_t h_stride_2d = (C / H) * (C / H);
for (size_t t = 0; t < T; t++) {
size_t t_offset = t * t_stride;
for (size_t h = 0; h < H; h++) {
size_t h_offset = h * h_stride;
size_t t_h_offset = t_offset + h_offset;
size_t h_2d_offset = h * h_stride_2d;
for (size_t i = 0; i < C / H; i++) {
size_t t_h_i_offset = t_h_offset + i;
size_t h_i_offset = h_offset + i;
size_t h_2d_i_offset = h_2d_offset + i * h_stride;
auto k_val = SET1(k[t_h_i_offset]);
auto r_val = SET1(r[t_h_i_offset]);
auto time_f_val = SET1(time_f[h_i_offset]);
auto time_decay_val = SET1(time_decay[h_i_offset]);
for (size_t j = 0; j < C / H; j += SIMD_WIDTH) {
size_t t_h_j_offset = t_h_offset + j;
size_t h_2d_i_j_offset = h_2d_i_offset + j;
auto v_val = LOAD(&v[t_h_j_offset]);
auto kv_val = MULTIPLY(v_val, k_val);
auto prev_state_val = LOAD(&state[h_2d_i_j_offset]);
auto temp_val = MULTADD(kv_val, time_f_val, prev_state_val);
auto prev_result_data = LOAD(&result_data[t_h_j_offset]);
STORE(&result_data[t_h_j_offset], MULTADD(temp_val, r_val, prev_result_data));
STORE(&state[h_2d_i_j_offset], MULTADD(prev_state_val, time_decay_val, kv_val));
}
}
}
}
// Suppress "unused parameter" warnings.
(void) src;
(void) ith;
(void) nth;
(void) userdata;
}
// Parameters:
// - T: sequence length
// - C: channel count, same as n_embed
// - H: head count
// - S: head size
// Shapes (in ggml order):
// - x: [C, T, 1, 1]
// - k: [1, S, H, T]
// - v: [S, 1, H, T]
// - r: [S, 1, H, T]
// - time_f: [1, S, H, 1]
// - time_decay: [1, S, H, 1]
// - state: [S * S * H, 1, 1, 1]
// - result: same as x
// time_f and time_decay must be preprocessed as neccessary -- exp() applied, etc.
// state will be written to.
static struct ggml_tensor * rwkv_wkv_v5(
struct ggml_context * ctx,
const size_t T,
const size_t C,
const size_t H,
const size_t S,
struct ggml_tensor * x,
struct ggml_tensor * k,
struct ggml_tensor * v,
struct ggml_tensor * r,
// time_first for v5.1, time_faaaa for v5.2.
struct ggml_tensor * time_f,
struct ggml_tensor * time_decay,
struct ggml_tensor * state
) {
GGML_ASSERT(x->type == GGML_TYPE_F32);
GGML_ASSERT(k->type == GGML_TYPE_F32);
GGML_ASSERT(v->type == GGML_TYPE_F32);
GGML_ASSERT(r->type == GGML_TYPE_F32);
GGML_ASSERT(time_f->type == GGML_TYPE_F32);
GGML_ASSERT(time_decay->type == GGML_TYPE_F32);
GGML_ASSERT(state->type == GGML_TYPE_F32);
GGML_ASSERT(ggml_is_contiguous(x));
GGML_ASSERT(ggml_is_contiguous(k));
GGML_ASSERT(ggml_is_contiguous(v));
GGML_ASSERT(ggml_is_contiguous(r));
GGML_ASSERT(ggml_is_contiguous(time_f));
GGML_ASSERT(ggml_is_contiguous(time_decay));
GGML_ASSERT(ggml_is_contiguous(state));
GGML_ASSERT(x->ne[0] == C && x->ne[1] == T && x->ne[2] == 1 && x->ne[3] == 1);
GGML_ASSERT(k->ne[0] == 1 && k->ne[1] == S && k->ne[2] == H && k->ne[3] == T);
GGML_ASSERT(v->ne[0] == S && v->ne[1] == 1 && v->ne[2] == H && v->ne[3] == T);
GGML_ASSERT(r->ne[0] == S && r->ne[1] == 1 && r->ne[2] == H && r->ne[3] == T);
GGML_ASSERT(ggml_nelements(state) == S * S * H);
k = ggml_cont_inplace(ctx, ggml_transpose(ctx, k));
v = ggml_cont_inplace(ctx, ggml_transpose(ctx, v));
r = ggml_cont_inplace(ctx, ggml_transpose(ctx, r));
struct ggml_tensor * result = ggml_map_custom1(
ctx,
x,
rwkv_wkv_v5_impl,
1,
NULL
);
result->src[1] = k;
result->src[2] = v;
result->src[3] = r;
result->src[4] = time_f;
result->src[5] = time_decay;
// GGML_MAX_SRC must be increased from 6 to 8 for this.
result->src[6] = state;
return result;
}