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llama : only copy used KV cache in get / set state (ggerganov#1272)
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* llama : only copy used KV cache in get / set state

* switch to ggml for copying k, v

* avoid designated initializers
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@ejones
ejones authored May 3, 2023
1 parent 2485d7a commit e216aa0
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Showing 2 changed files with 80 additions and 23 deletions.
98 changes: 77 additions & 21 deletions llama.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1285,6 +1285,9 @@ static bool llama_eval_internal(
//embd_w.resize(n_vocab*N);
//memcpy(embd_w.data(), ggml_get_data(inpL), sizeof(float)*n_vocab*N);

// update kv token count
lctx.model.kv_self.n = n_past + N;

// extract logits
{
auto & logits_out = lctx.logits;
Expand Down Expand Up @@ -2401,7 +2404,7 @@ void llama_set_rng_seed(struct llama_context * ctx, int seed) {
ctx->rng.seed(seed);
}

// Returns the size of the state
// Returns the *maximum* size of the state
size_t llama_get_state_size(const struct llama_context * ctx) {
// we don't know size of rng until we actually serialize it. so reserve more than enough memory for its serialized state.
// for reference, std::mt19937(1337) serializes to 6701 bytes.
Expand Down Expand Up @@ -2480,21 +2483,51 @@ size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dest) {

// copy kv cache
{
const size_t kv_size = ctx->model.kv_self.buf.size;
const auto & kv_self = ctx->model.kv_self;
const auto & hparams = ctx->model.hparams;
const int n_layer = hparams.n_layer;
const int n_embd = hparams.n_embd;
const int n_ctx = hparams.n_ctx;

const size_t kv_size = kv_self.buf.size;
const int kv_ntok = llama_get_kv_cache_token_count(ctx);

memcpy(out, &kv_size, sizeof(kv_size)); out += sizeof(kv_size);
memcpy(out, &kv_ntok, sizeof(kv_ntok)); out += sizeof(kv_ntok);

if (kv_size) {
memcpy(out, ctx->model.kv_self.buf.addr, kv_size); out += kv_size;
const size_t elt_size = ggml_element_size(kv_self.k);
char buffer[4096];
ggml_context * cpy_ctx = ggml_init({ sizeof(buffer), buffer, /* no_alloc */ true });
ggml_cgraph gf{};
gf.n_threads = 1;

ggml_tensor * kout3d = ggml_new_tensor_3d(cpy_ctx, kv_self.k->type, n_embd, kv_ntok, n_layer);
kout3d->data = out;
out += ggml_nbytes(kout3d);

ggml_tensor * vout3d = ggml_new_tensor_3d(cpy_ctx, kv_self.v->type, kv_ntok, n_embd, n_layer);
vout3d->data = out;
out += ggml_nbytes(vout3d);

ggml_tensor * k3d = ggml_view_3d(cpy_ctx, kv_self.k,
n_embd, kv_ntok, n_layer,
elt_size*n_embd, elt_size*n_embd*n_ctx, 0);

ggml_tensor * v3d = ggml_view_3d(cpy_ctx, kv_self.v,
kv_ntok, n_embd, n_layer,
elt_size*n_ctx, elt_size*n_ctx*n_embd, 0);

ggml_build_forward_expand(&gf, ggml_cpy(cpy_ctx, k3d, kout3d));
ggml_build_forward_expand(&gf, ggml_cpy(cpy_ctx, v3d, vout3d));
ggml_graph_compute(cpy_ctx, &gf);
}
}

const size_t written = out - dest;
const size_t expected = llama_get_state_size(ctx);
const size_t max_size = llama_get_state_size(ctx);

LLAMA_ASSERT(written == expected);
LLAMA_ASSERT(written <= max_size);

return written;
}
Expand Down Expand Up @@ -2552,32 +2585,55 @@ size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {

// set kv cache
{
const auto & kv_self = ctx->model.kv_self;
const auto & hparams = ctx->model.hparams;
const int n_layer = hparams.n_layer;
const int n_embd = hparams.n_embd;
const int n_ctx = hparams.n_ctx;

size_t kv_size;
int kv_ntok;

memcpy(&kv_size, in, sizeof(kv_size)); in += sizeof(kv_size);
memcpy(&kv_ntok, in, sizeof(kv_ntok)); in += sizeof(kv_ntok);

if (kv_size) {
LLAMA_ASSERT(ctx->model.kv_self.buf.size == kv_size);
LLAMA_ASSERT(kv_self.buf.size == kv_size);

const size_t elt_size = ggml_element_size(kv_self.k);
char buffer[4096];
ggml_context * cpy_ctx = ggml_init({ sizeof(buffer), buffer, /* no_alloc */ true });
ggml_cgraph gf{};
gf.n_threads = 1;

ggml_tensor * kin3d = ggml_new_tensor_3d(cpy_ctx, kv_self.k->type, n_embd, kv_ntok, n_layer);
kin3d->data = (void *) in;
in += ggml_nbytes(kin3d);

void * k_data = ctx->model.kv_self.k->data; // remember data pointers
void * v_data = ctx->model.kv_self.v->data; // because their value is stored in buf and overwritten by memcpy
ggml_tensor * vin3d = ggml_new_tensor_3d(cpy_ctx, kv_self.v->type, kv_ntok, n_embd, n_layer);
vin3d->data = (void *) in;
in += ggml_nbytes(vin3d);

memcpy(ctx->model.kv_self.buf.addr, in, kv_size); in += kv_size;
ggml_tensor * k3d = ggml_view_3d(cpy_ctx, kv_self.k,
n_embd, kv_ntok, n_layer,
elt_size*n_embd, elt_size*n_embd*n_ctx, 0);

ctx->model.kv_self.k->data = k_data; // restore correct data pointers
ctx->model.kv_self.v->data = v_data;
ggml_tensor * v3d = ggml_view_3d(cpy_ctx, kv_self.v,
kv_ntok, n_embd, n_layer,
elt_size*n_ctx, elt_size*n_ctx*n_embd, 0);

ggml_build_forward_expand(&gf, ggml_cpy(cpy_ctx, kin3d, k3d));
ggml_build_forward_expand(&gf, ggml_cpy(cpy_ctx, vin3d, v3d));
ggml_graph_compute(cpy_ctx, &gf);
}

ctx->model.kv_self.n = kv_ntok;
}

const size_t nread = in - src;
const size_t expected = llama_get_state_size(ctx);
const size_t max_size = llama_get_state_size(ctx);

LLAMA_ASSERT(nread == expected);
LLAMA_ASSERT(nread <= max_size);

return nread;
}
Expand Down Expand Up @@ -2620,14 +2676,14 @@ bool llama_load_session_file(struct llama_context * ctx, const char * path_sessi
// restore the context state
{
const size_t n_state_size_cur = file.size - file.tell();
const size_t n_state_size_exp = llama_get_state_size(ctx);
const size_t n_state_size_max = llama_get_state_size(ctx);

if (n_state_size_cur != n_state_size_exp) {
fprintf(stderr, "%s : the state size in session file didn't match! expected %zu, got %zu\n", __func__, n_state_size_exp, n_state_size_cur);
if (n_state_size_cur > n_state_size_max) {
fprintf(stderr, "%s : the state size in session file is too big! max %zu, got %zu\n", __func__, n_state_size_max, n_state_size_cur);
return false;
}

std::vector<uint8_t> state_data(n_state_size_cur);
std::vector<uint8_t> state_data(n_state_size_max);
file.read_raw(state_data.data(), n_state_size_cur);

llama_set_state_data(ctx, state_data.data());
Expand All @@ -2650,12 +2706,12 @@ bool llama_save_session_file(struct llama_context * ctx, const char * path_sessi

// save the context state
{
const size_t n_state_size = llama_get_state_size(ctx);
const size_t n_state_size_max = llama_get_state_size(ctx);

std::vector<uint8_t> state_data(n_state_size);
llama_copy_state_data(ctx, state_data.data());
std::vector<uint8_t> state_data(n_state_size_max);
const size_t n_state_size_cur = llama_copy_state_data(ctx, state_data.data());

file.write_raw(state_data.data(), n_state_size);
file.write_raw(state_data.data(), n_state_size_cur);
}

return true;
Expand Down
5 changes: 3 additions & 2 deletions llama.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
#define LLAMA_FILE_MAGIC 'ggjt'
#define LLAMA_FILE_MAGIC_UNVERSIONED 'ggml'
#define LLAMA_SESSION_MAGIC 'ggsn'
#define LLAMA_SESSION_VERSION 0
#define LLAMA_SESSION_VERSION 1

#ifdef __cplusplus
extern "C" {
Expand Down Expand Up @@ -127,7 +127,8 @@ extern "C" {
// Sets the current rng seed.
LLAMA_API void llama_set_rng_seed(struct llama_context * ctx, int seed);

// Returns the size in bytes of the state (rng, logits, embedding and kv_cache)
// Returns the maximum size in bytes of the state (rng, logits, embedding
// and kv_cache) - will often be smaller after compacting tokens
LLAMA_API size_t llama_get_state_size(const struct llama_context * ctx);

// Copies the state to the specified destination address.
Expand Down

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