Added api for getting/setting the kv_cache (#685)

The api provides access methods for retrieving the current memory buffer for the kv_cache and its token number.
It also contains a method for setting the kv_cache from a memory buffer.

This makes it possible to load/save history - maybe support --cache-prompt paramater as well?

Co-authored-by: Pavol Rusnak <pavol@rusnak.io>
pull/706/head master-e986f94
Christian Falch 1 year ago committed by GitHub
parent c0bb1d3ce2
commit e986f94829
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GPG Key ID: 4AEE18F83AFDEB23

@ -1668,6 +1668,33 @@ int llama_model_quantize(
return 0;
}
// Returns the KV cache that will contain the context for the
// ongoing prediction with the model.
const uint8_t * llama_get_kv_cache(struct llama_context * ctx) {
return ctx->model.kv_self.buf.data();
}
// Returns the size of the KV cache
size_t llama_get_kv_cache_size(struct llama_context * ctx) {
return ctx->model.kv_self.buf.size();
}
int llama_get_kv_cache_token_count(struct llama_context * ctx) {
return ctx->model.kv_self.n;
}
// Sets the KV cache containing the current context for the model
void llama_set_kv_cache(
struct llama_context * ctx,
const uint8_t * kv_cache,
size_t n_size,
int n_token_count) {
// Make sure we have the same kv cache setup
LLAMA_ASSERT(ctx->model.kv_self.buf.size() == n_size);
memcpy(ctx->model.kv_self.buf.data(), kv_cache, n_size);
ctx->model.kv_self.n = n_token_count;
}
int llama_eval(
struct llama_context * ctx,
const llama_token * tokens,

@ -83,6 +83,23 @@ extern "C" {
const char * fname_out,
int itype);
// Returns the KV cache that will contain the context for the
// ongoing prediction with the model.
LLAMA_API const uint8_t * llama_get_kv_cache(struct llama_context * ctx);
// Returns the size of the KV cache
LLAMA_API size_t llama_get_kv_cache_size(struct llama_context * ctx);
// Returns the number of tokens in the KV cache
LLAMA_API int llama_get_kv_cache_token_count(struct llama_context * ctx);
// Sets the KV cache containing the current context for the model
LLAMA_API void llama_set_kv_cache(
struct llama_context * ctx,
const uint8_t * kv_cache,
size_t n_size,
int n_token_count);
// Run the llama inference to obtain the logits and probabilities for the next token.
// tokens + n_tokens is the provided batch of new tokens to process
// n_past is the number of tokens to use from previous eval calls

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