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ggml: Add unary operator Exp

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Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
This commit is contained in:
Molly Sophia 2024-08-02 16:29:16 +08:00
parent 0e5ac349f8
commit 5732de89b7
2 changed files with 72 additions and 1 deletions
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9
ggml/include/ggml.h
View file

@ -546,6 +546,7 @@ extern "C" {
GGML_UNARY_OP_SILU,
GGML_UNARY_OP_HARDSWISH,
GGML_UNARY_OP_HARDSIGMOID,
GGML_UNARY_OP_EXP,
GGML_UNARY_OP_COUNT,
};
@ -1139,6 +1140,14 @@ extern "C" {
struct ggml_context * ctx,
struct ggml_tensor * a);
GGML_API struct ggml_tensor * ggml_exp(
struct ggml_context * ctx,
struct ggml_tensor * a);
GGML_API struct ggml_tensor * ggml_exp_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
// normalize along rows
GGML_API struct ggml_tensor * ggml_norm(
struct ggml_context * ctx,

64
ggml/src/ggml.c
View file

@ -2324,6 +2324,7 @@ inline static void ggml_vec_sigmoid_f32 (const int n, float * y, const float * x
// TODO: optimize performance
inline static void ggml_vec_hardswish_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i] * fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_hardsigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_exp_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = expf(x[i]); }
static const float GELU_COEF_A = 0.044715f;
static const float GELU_QUICK_COEF = -1.702f;
@ -2963,9 +2964,10 @@ static const char * GGML_UNARY_OP_NAME[GGML_UNARY_OP_COUNT] = {
"SILU",
"HARDSWISH",
"HARDSIGMOID",
"EXP",
};
static_assert(GGML_UNARY_OP_COUNT == 13, "GGML_UNARY_OP_COUNT != 13");
static_assert(GGML_UNARY_OP_COUNT == 14, "GGML_UNARY_OP_COUNT != 14");
static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN");
@ -5359,6 +5361,19 @@ struct ggml_tensor * ggml_hardsigmoid(
return ggml_unary(ctx, a, GGML_UNARY_OP_HARDSIGMOID);
}
// ggml exp
struct ggml_tensor * ggml_exp(
struct ggml_context * ctx,
struct ggml_tensor * a) {
return ggml_unary(ctx, a, GGML_UNARY_OP_EXP);
}
struct ggml_tensor * ggml_exp_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a) {
return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_EXP);
}
// ggml_norm
static struct ggml_tensor * ggml_norm_impl(
@ -12021,6 +12036,48 @@ static void ggml_compute_forward_hardsigmoid(
}
}
static void ggml_compute_forward_exp_f32(
const struct ggml_compute_params * params,
struct ggml_tensor * dst) {
const struct ggml_tensor * src0 = dst->src[0];
if (params->ith != 0) {
return;
}
assert(ggml_is_contiguous_1(src0));
assert(ggml_is_contiguous_1(dst));
assert(ggml_are_same_shape(src0, dst));
const int n = ggml_nrows(src0);
const int nc = src0->ne[0];
for (int i = 0; i < n; i++) {
ggml_vec_exp_f32(nc,
(float *) ((char *) dst->data + i*( dst->nb[1])),
(float *) ((char *) src0->data + i*(src0->nb[1])));
}
}
static void ggml_compute_forward_exp(
const struct ggml_compute_params * params,
struct ggml_tensor * dst) {
const struct ggml_tensor * src0 = dst->src[0];
switch (src0->type) {
case GGML_TYPE_F32:
{
ggml_compute_forward_exp_f32(params, dst);
} break;
default:
{
GGML_ABORT("fatal error");
}
}
}
// ggml_compute_forward_norm
@ -16599,6 +16656,10 @@ static void ggml_compute_forward_unary(
{
ggml_compute_forward_hardsigmoid(params, dst);
} break;
case GGML_UNARY_OP_EXP:
{
ggml_compute_forward_exp(params, dst);
} break;
default:
{
GGML_ABORT("fatal error");
@ -18990,6 +19051,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
case GGML_UNARY_OP_SIGMOID:
case GGML_UNARY_OP_HARDSWISH:
case GGML_UNARY_OP_HARDSIGMOID:
case GGML_UNARY_OP_EXP:
{
n_tasks = 1;
} break;