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https://git.adityakumar.xyz/llama.cpp.git
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llama : add api for getting/setting the complete state: rng, logits, embedding and kv_cache (#1105)
* reserve correct size for logits * add functions to get and set the whole llama state: including rng, logits, embedding and kv_cache * remove unused variables * remove trailing whitespace * fix comment
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2 changed files with 133 additions and 1 deletions
122
llama.cpp
122
llama.cpp
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@ -27,6 +27,7 @@
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#include <thread>
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#include <atomic>
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#include <mutex>
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#include <sstream>
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#define LLAMA_USE_SCRATCH
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#define LLAMA_MAX_SCRATCH_BUFFERS 16
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@ -1787,7 +1788,7 @@ struct llama_context * llama_init_from_file(
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if (params.logits_all) {
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ctx->logits.reserve(hparams.n_ctx*hparams.n_vocab);
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} else {
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ctx->logits.reserve(hparams.n_ctx);
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ctx->logits.reserve(hparams.n_vocab);
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}
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if (params.embedding){
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@ -2252,3 +2253,122 @@ const char * llama_print_system_info(void) {
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std::vector<std::pair<std::string, struct ggml_tensor *>>& llama_internal_get_tensor_map(struct llama_context * ctx) {
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return ctx->model.tensors_by_name;
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}
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// Returns the size of the state
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size_t llama_get_state_size(struct llama_context * ctx) {
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const size_t s_bool = sizeof(int32_t);
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// we don't know size of rng until we actually serialize it. so reserve more than enough memory for its serialized state.
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// for reference, std::mt19937(1337) serializes to 6701 bytes.
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const size_t s_rng_size = sizeof(size_t);
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const size_t s_rng = 64*1024;
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const size_t s_logits_capacity = sizeof(size_t);
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const size_t s_logits_size = sizeof(size_t);
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const size_t s_logits = ctx->logits.capacity() * sizeof(float);
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const size_t s_embedding_size = sizeof(size_t);
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const size_t s_embedding = ctx->embedding.size() * sizeof(float);
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const size_t s_kv_size = sizeof(size_t);
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const size_t s_kv_ntok = sizeof(int);
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const size_t s_kv = llama_get_kv_cache_size(ctx);
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const size_t s_total = (
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+ s_rng_size
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+ s_rng
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+ s_logits_capacity
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+ s_logits_size
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+ s_logits
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+ s_embedding_size
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+ s_embedding
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+ s_kv_size
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+ s_kv_ntok
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+ s_kv
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);
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return s_total;
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}
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// Copies the state to the specified destination address
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size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dest) {
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std::stringstream rng_ss;
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rng_ss << ctx->rng;
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const size_t rng_size = rng_ss.str().size();
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char rng_buf[64*1024];
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memset(&rng_buf[0], 0, 64*1024);
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memcpy(&rng_buf[0], rng_ss.str().data(), rng_ss.str().size());
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const size_t logits_capacity = ctx->logits.capacity();
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const size_t logits_size = ctx->logits.size();
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const size_t embedding_size = ctx->embedding.size();
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const size_t kv_size = llama_get_kv_cache_size(ctx);
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const int kv_ntok = llama_get_kv_cache_token_count(ctx);
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uint8_t * out = dest;
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memcpy(out, &rng_size, sizeof(size_t)); out += sizeof(size_t);
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memcpy(out, &rng_buf[0], 64*1024); out += 64*1024;
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memcpy(out, &logits_capacity, sizeof(size_t)); out += sizeof(size_t);
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memcpy(out, &logits_size, sizeof(size_t)); out += sizeof(size_t);
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if (logits_size) {
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memcpy(out, ctx->logits.data(), logits_size * sizeof(float));
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}
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out += logits_capacity * sizeof(float);
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memcpy(out, &embedding_size, sizeof(size_t)); out += sizeof(size_t);
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if (embedding_size) {
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memcpy(out, ctx->embedding.data(), embedding_size * sizeof(float)); out += embedding_size * sizeof(float);
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}
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memcpy(out, &kv_size, sizeof(size_t)); out += sizeof(size_t);
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memcpy(out, &kv_ntok, sizeof(int)); out += sizeof(int);
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if (kv_size) {
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memcpy(out, llama_get_kv_cache(ctx), kv_size); out += kv_size;
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}
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const size_t written = out - dest;
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const size_t expected = llama_get_state_size(ctx);
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LLAMA_ASSERT(written == expected);
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return written;
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}
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// Sets the state reading from the specified source address
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size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
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size_t rng_size;
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char rng_buf[64*1024];
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std::stringstream rng_ss;
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const uint8_t * in = src;
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memcpy(&rng_size, in, sizeof(size_t)); in += sizeof(size_t);
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memcpy(&rng_buf[0], in, 64*1024); in += 64*1024;
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rng_ss.str(std::string(&rng_buf[0], rng_size));
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rng_ss >> ctx->rng;
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LLAMA_ASSERT(rng_ss.fail() == false);
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size_t logits_capacity;
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size_t logits_size;
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size_t embedding_size;
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size_t kv_size;
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int kv_ntok;
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memcpy(&logits_capacity, in, sizeof(size_t)); in += sizeof(size_t);
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memcpy(&logits_size, in, sizeof(size_t)); in += sizeof(size_t);
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LLAMA_ASSERT(ctx->logits.capacity() == logits_capacity);
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if (logits_size) {
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ctx->logits.resize(logits_size);
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memcpy(ctx->logits.data(), in, logits_size * sizeof(float));
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}
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in += logits_capacity * sizeof(float);
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memcpy(&embedding_size, in, sizeof(size_t)); in += sizeof(size_t);
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LLAMA_ASSERT(ctx->embedding.capacity() == embedding_size);
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if (embedding_size) {
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memcpy(ctx->embedding.data(), in, embedding_size * sizeof(float));
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in += embedding_size * sizeof(float);
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}
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memcpy(&kv_size, in, sizeof(size_t)); in += sizeof(size_t);
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memcpy(&kv_ntok, in, sizeof(int)); in += sizeof(int);
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if (kv_size) {
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LLAMA_ASSERT(ctx->model.kv_self.buf.size == kv_size);
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void * k_data = ctx->model.kv_self.k->data; // remember data pointers
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void * v_data = ctx->model.kv_self.v->data; // because their value is stored in buf and overwritten by memcpy
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memcpy(ctx->model.kv_self.buf.addr, in, kv_size);
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ctx->model.kv_self.k->data = k_data; // restore correct data pointers
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ctx->model.kv_self.v->data = v_data;
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in += kv_size;
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}
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ctx->model.kv_self.n = kv_ntok;
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const size_t nread = in - src;
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const size_t expected = llama_get_state_size(ctx);
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LLAMA_ASSERT(nread == expected);
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return nread;
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}
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12
llama.h
12
llama.h
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@ -129,6 +129,18 @@ extern "C" {
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size_t n_size,
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int n_token_count);
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// Returns the size in bytes of the state (rng, logits, embedding and kv_cache)
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LLAMA_API size_t llama_get_state_size(struct llama_context * ctx);
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// Copies the state to the specified destination address.
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// Destination needs to have allocated enough memory.
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// Returns the number of bytes copied
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LLAMA_API size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dest);
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// Set the state reading from the specified address
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// Returns the number of bytes read
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LLAMA_API size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src);
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// Run the llama inference to obtain the logits and probabilities for the next token.
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// tokens + n_tokens is the provided batch of new tokens to process
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// n_past is the number of tokens to use from previous eval calls
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