// Test for state restore with fragmented KV cache
// This tests the fix for: https://github.com/ggml-org/llama.cpp/issues/17527
// The issue was that state restore required contiguous KV cache slots,
// which fails when the cache is fragmented.
//
// The fix changes find_slot(ubatch, true) to find_slot(ubatch, false)
// in state_read_meta(), allowing non-contiguous slot allocation.
#include "arg.h"
#include "common.h"
#include "llama.h"
#include <vector>
#include <cstdio>
#include <cstring>
int main(int argc, char ** argv) {
common_params params;
params.sampling.seed = 1234;
params.kv_unified = true;
params.n_parallel = 3;
params.n_ctx = 256;
common_init();
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
return 1;
}
// init
ggml_backend_load_all();
common_init_result_ptr llama_init = common_init_from_params(params);
llama_model * model = llama_init->model();
llama_context * ctx = llama_init->context();
if (model == nullptr || ctx == nullptr) {
fprintf(stderr, "%s : failed to init\n", __func__);
return 1;
}
GGML_UNUSED(model);
// tokenize prompt
std::vector<llama_token> tokens(70, 1);
// interleave the 3 sequences:
// 01201230123...
llama_batch batch = llama_batch_init(params.n_parallel*tokens.size(), 0, 1);
for (size_t i = 0; i < tokens.size(); i++) {
for (int s = 0; s < params.n_parallel; ++s) {
common_batch_add(batch, tokens[i], i, {s}, false);
}
}
batch.logits[batch.n_tokens - 1] = true;
if (llama_decode(ctx, batch)) {
fprintf(stderr, "%s : failed to decode seq 0\n", __func__);
return 1;
}
fprintf(stderr, "%s : processed prompt on seq 0, 1, 2 (%zu tokens each)\n", __func__, tokens.size());
// Save state of seq 1
std::vector<uint8_t> seq_state(llama_state_seq_get_size(ctx, 1));
const size_t ncopy = llama_state_seq_get_data(ctx, seq_state.data(), seq_state.size(), 1);
if (ncopy != seq_state.size()) {
fprintf(stderr, "%s : failed to save seq 1 state\n", __func__);
return 1;
}
fprintf(stderr, "%s : saved seq 1 state, %zu bytes\n", __func__, ncopy);
// clear seq 1 to create a "hole" in the KV cache (fragmentation)
// 0.20.20.20.2....
llama_memory_t mem = llama_get_memory(ctx);
llama_memory_seq_rm(mem, 1, -1, -1);
fprintf(stderr, "%s : cleared seq 1 to create fragmentation\n", __func__);
// Now the cache has holes where seq 1 was
// This creates fragmentation - there's no contiguous block large enough
// for the seq 1 state if we only look for contiguous slots
// Restore seq 1 state into seq 1 (should work with non-contiguous allocation)
// We use seq 1 since it's a valid sequence ID (0 to n_parallel-1)
// Before the fix, this would fail with "failed to find available cells in kv cache"
const size_t nset = llama_state_seq_set_data(ctx, seq_state.data(), seq_state.size(), 1);
if (nset != seq_state.size()) {
fprintf(stderr, "%s : FAILED to restore seq state into fragmented cache (got %zu, expected %zu)\n",
__func__, nset, seq_state.size());
fprintf(stderr, "%s : This is the bug - state restore fails with fragmented KV cache\n", __func__);
llama_batch_free(batch);
return 1;
}
fprintf(stderr, "%s : restored state into seq 1, %zu bytes\n", __func__, nset);
// Verify we can decode with the restored state
// Generate one token to verify the restored state is usable
auto sparams = llama_sampler_chain_default_params();
llama_sampler * smpl = llama_sampler_chain_init(sparams);
llama_sampler_chain_add(smpl, llama_sampler_init_dist(params.sampling.seed));
auto next_token = llama_sampler_sample(smpl, ctx, -1);
auto next_token_str = common_token_to_piece(ctx, next_token);
common_batch_clear(batch);
common_batch_add(batch, next_token, (int)tokens.size(), {1}, true);
if (llama_decode(ctx, batch)) {
fprintf(stderr, "%s : failed to decode with restored state\n", __func__);
llama_sampler_free(smpl);
llama_batch_free(batch);
return 1;
}
fprintf(stderr, "%s : successfully decoded with restored state, generated: '%s'\n", __func__, next_token_str.c_str());
fprintf(stderr, "%s : SUCCESS - state restore works with fragmented KV cache\n", __func__);
llama_sampler_free(smpl);
llama_batch_free(batch);
return 0;
}