vbatts/llama.cpp
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llama : save and restore kv cache for single seq id (#6341)

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* llama : save and restore kv cache for single seq id

* remove trailing whitespace

* respond error in case there's no space in the kv cache

* add kv seq save restore to test case

* add --slot-save-path arg to enable save restore and restrict save location

* Returning 0 for some cases, instead of asserting.

* cleanup error cases

* rename sequence state functions

* rename state get set functions

* add previous function names back in with DEPRECATED notice

* update doc

* adjust endpoints to preferred style

* fix restoring zero cell count

* handle seq rm return value

* unused param

* keep in the size check

* fix return types

* add server test case for slot save restore

* cleanup

* add cake

* cleanup style

* add special

* removing a whole sequence never fails

* move sequence state file functionality from server to llama to match session api and add version tags

* catch exceptions on save as well

* error log messages

* check types for stricter restore

* update server doc

* readme : update API changes date

* strict filename validation

* move include, reject bom as well

* also reject empty filename

* reject whitespace and trailing dot

---------

Co-authored-by: Martin Evans <martindevans@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Jan Boon 2024-04-08 20:43:30 +08:00 • committed by GitHub
parent 87fb5b4234
commit beea6e1b16
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GPG key ID: B5690EEEBB952194
11 changed files with 1086 additions and 31 deletions
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101
examples/save-load-state/save-load-state.cpp
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@ -24,6 +24,7 @@ int main(int argc, char ** argv) {
std::string result0;
std::string result1;
std::string result2;
// init
llama_model * model;
@ -44,8 +45,8 @@ int main(int argc, char ** argv) {
// save state (rng, logits, embedding and kv_cache) to file
{
std::vector<uint8_t> state_mem(llama_get_state_size(ctx));
const size_t written = llama_copy_state_data(ctx, state_mem.data());
std::vector<uint8_t> state_mem(llama_state_get_size(ctx));
const size_t written = llama_state_get_data(ctx, state_mem.data());
FILE *fp_write = fopen("dump_state.bin", "wb");
fwrite(state_mem.data(), 1, written, fp_write);
@ -97,13 +98,13 @@ int main(int argc, char ** argv) {
// load state (rng, logits, embedding and kv_cache) from file
{
std::vector<uint8_t> state_mem(llama_get_state_size(ctx2));
std::vector<uint8_t> state_mem(llama_state_get_size(ctx2));
FILE * fp_read = fopen("dump_state.bin", "rb");
const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
fclose(fp_read);
if (read != llama_set_state_data(ctx2, state_mem.data())) {
if (read != llama_state_set_data(ctx2, state_mem.data())) {
fprintf(stderr, "\n%s : failed to read state\n", __func__);
llama_free(ctx2);
llama_free_model(model);
@ -141,16 +142,104 @@ int main(int argc, char ** argv) {
n_past += 1;
}
printf("\n");
printf("\n\n");
llama_free(ctx2);
llama_free_model(model);
if (result0 != result1) {
fprintf(stderr, "\n%s : error : the 2 generations are different\n", __func__);
return 1;
}
// make new context
auto* ctx3 = llama_new_context_with_model(model, llama_context_params_from_gpt_params(params));
printf("\nsingle seq run: %s", params.prompt.c_str());
// load state (rng, logits, embedding and kv_cache) from file
{
std::vector<uint8_t> state_mem(llama_state_get_size(ctx3));
FILE * fp_read = fopen("dump_state.bin", "rb");
const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
fclose(fp_read);
if (read != llama_state_set_data(ctx3, state_mem.data())) {
fprintf(stderr, "\n%s : failed to read state\n", __func__);
llama_free(ctx3);
llama_free_model(model);
return 1;
}
fprintf(stderr, "%s : deserialized state from %zd out of a maximum of %zd bytes\n", __func__, read, state_mem.size());
}
// restore state (last tokens)
n_past = n_past_saved;
// save seq 0 and load into seq 1
{
// save kv of seq 0
std::vector<uint8_t> seq_store(llama_state_seq_get_size(ctx3, 0));
const size_t ncopy = llama_state_seq_get_data(ctx3, seq_store.data(), 0);
if (ncopy != seq_store.size()) {
fprintf(stderr, "\n%s : seq copy data length %zd does not match expected length %zd\n", __func__, ncopy, seq_store.size());
llama_free(ctx3);
llama_free_model(model);
return 1;
}
fprintf(stderr, "%s : seq 0 copied, %zd bytes\n", __func__, ncopy);
// erase whole kv
llama_kv_cache_clear(ctx3);
fprintf(stderr, "%s : kv cache cleared\n", __func__);
// restore kv into seq 1
const size_t nset = llama_state_seq_set_data(ctx3, seq_store.data(), 1);
if (nset != seq_store.size()) {
fprintf(stderr, "\n%s : seq set data length %zd does not match expected length %zd\n", __func__, nset, seq_store.size());
llama_free(ctx3);
llama_free_model(model);
return 1;
}
fprintf(stderr, "%s : seq 1 restored, %zd bytes\n", __func__, nset);
}
// third run with seq 1 instead of 0
for (auto i = 0; i < params.n_predict; i++) {
auto * logits = llama_get_logits(ctx3);
auto n_vocab = llama_n_vocab(model);
std::vector<llama_token_data> candidates;
candidates.reserve(n_vocab);
for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
candidates.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f});
}
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
auto next_token = llama_sample_token(ctx3, &candidates_p);
auto next_token_str = llama_token_to_piece(ctx3, next_token);
printf("%s", next_token_str.c_str());
result2 += next_token_str;
if (llama_decode(ctx3, llama_batch_get_one(&next_token, 1, n_past, 1))) {
fprintf(stderr, "\n%s : failed to evaluate\n", __func__);
llama_free(ctx3);
llama_free_model(model);
return 1;
}
n_past += 1;
}
printf("\n");
llama_free(ctx3);
llama_free_model(model);
if (result0 != result2) {
fprintf(stderr, "\n%s : error : the seq restore generation is different\n", __func__);
return 1;
}
fprintf(stderr, "\n%s : success\n", __func__);
return 0;