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https://github.com/ggerganov/llama.cpp.git
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llama : allow exporting a view of the KV cache (#4180)
* Allow exporting a view of the KV cache * Allow dumping the sequences per cell in common * Track max contiguous cells value and position as well * Fix max contiguous empty cells index calculation Make dump functions deal with lengths or sequences counts > 10 better * Fix off by one error in dump_kv_cache_view * Add doc comments for KV cache view functions Eliminate cell sequence struct; use llama_seq_id directly Minor cleanups
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@ -12,6 +12,7 @@
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#include <regex>
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#include <sstream>
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <vector>
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#include <cinttypes>
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@ -1386,3 +1387,77 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
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fprintf(stream, "typical_p: %f # default: 1.0\n", sparams.typical_p);
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fprintf(stream, "verbose_prompt: %s # default: false\n", params.verbose_prompt ? "true" : "false");
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}
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//
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// KV cache utils
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//
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void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size) {
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static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+";
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printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d",
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view.n_cells, view.n_max_seq, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
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llama_kv_cache_view_cell * c_curr = view.cells;
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llama_seq_id * cs_curr = view.cells_sequences;
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for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
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if (i % row_size == 0) {
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printf("\n%5d: ", i);
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}
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int seq_count = 0;
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for (int j = 0; j < view.n_max_seq; j++) {
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if (cs_curr[j] >= 0) { seq_count++; }
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}
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putchar(slot_chars[std::min(sizeof(slot_chars) - 2, size_t(seq_count))]);
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}
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printf("\n=== Done dumping\n");
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}
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void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size) {
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static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
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printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n",
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view.n_cells, view.n_max_seq, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
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std::unordered_map<llama_seq_id, size_t> seqs;
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llama_kv_cache_view_cell * c_curr = view.cells;
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llama_seq_id * cs_curr = view.cells_sequences;
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for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
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for (int j = 0; j < view.n_max_seq; j++) {
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if (cs_curr[j] < 0) { continue; }
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if (seqs.find(cs_curr[j]) == seqs.end()) {
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if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
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seqs[cs_curr[j]] = seqs.size();
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}
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}
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if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
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}
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printf("=== Sequence legend: ");
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for (const auto & it : seqs) {
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printf("%zu=%d, ", it.second, it.first);
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}
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printf("'+'=other sequence ids");
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c_curr = view.cells;
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cs_curr = view.cells_sequences;
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for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_max_seq) {
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if (i % row_size == 0) {
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printf("\n%5d: ", i);
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}
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for (int j = 0; j < view.n_max_seq; j++) {
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if (cs_curr[j] >= 0) {
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const auto & it = seqs.find(cs_curr[j]);
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putchar(it != seqs.end() ? int(slot_chars[it->second]) : '+');
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} else {
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putchar('.');
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}
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}
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putchar(' ');
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}
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printf("\n=== Done dumping\n");
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}
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@ -218,3 +218,13 @@ std::string get_sortable_timestamp();
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void dump_non_result_info_yaml(
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FILE * stream, const gpt_params & params, const llama_context * lctx,
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const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
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//
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// KV cache utils
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//
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// Dump the KV cache view with the number of sequences per cell.
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void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size = 80);
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// Dump the KV cache view showing individual sequences in each cell (long output).
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void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
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@ -172,6 +172,8 @@ int main(int argc, char ** argv) {
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int32_t n_total_gen = 0;
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int32_t n_cache_miss = 0;
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struct llama_kv_cache_view kvc_view = llama_kv_cache_view_init(ctx, n_clients);
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const auto t_main_start = ggml_time_us();
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LOG_TEE("%s: Simulating parallel requests from clients:\n", __func__);
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@ -201,6 +203,9 @@ int main(int argc, char ** argv) {
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LOG_TEE("Processing requests ...\n\n");
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while (true) {
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llama_kv_cache_view_update(ctx, &kvc_view);
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dump_kv_cache_view_seqs(kvc_view, 40);
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llama_batch_clear(batch);
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// decode any currently ongoing sequences
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89
llama.cpp
89
llama.cpp
@ -8805,6 +8805,95 @@ int llama_model_apply_lora_from_file(const struct llama_model * model, const cha
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}
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}
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struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_context * ctx, int32_t n_max_seq) {
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struct llama_kv_cache_view result = {
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/*.n_cells = */ 0,
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/*.n_max_seq = */ n_max_seq,
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/*.token_count = */ 0,
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/*.used_cells = */ llama_get_kv_cache_used_cells(ctx),
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/*.max_contiguous = */ 0,
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/*.max_contiguous_idx = */ -1,
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/*.cells = */ nullptr,
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/*.cells_sequences = */ nullptr,
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};
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return result;
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}
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void llama_kv_cache_view_free(struct llama_kv_cache_view * view) {
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if (view->cells != nullptr) {
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free(view->cells);
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view->cells = nullptr;
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}
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if (view->cells_sequences != nullptr) {
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free(view->cells_sequences);
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view->cells_sequences = nullptr;
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}
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}
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void llama_kv_cache_view_update(const struct llama_context * ctx, struct llama_kv_cache_view * view) {
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if (uint32_t(view->n_cells) < ctx->kv_self.size || view->cells == nullptr) {
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view->n_cells = int32_t(ctx->kv_self.size);
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void * p = realloc(view->cells, sizeof(struct llama_kv_cache_view_cell) * view->n_cells);
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GGML_ASSERT(p != nullptr && "Failed to alloc kv_cache_view cells");
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view->cells = (struct llama_kv_cache_view_cell *)p;
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p = realloc(view->cells_sequences, sizeof(llama_seq_id) * view->n_max_seq * view->n_cells);
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GGML_ASSERT(p != nullptr && "Failed to alloc kv_cache_view cells sequences");
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view->cells_sequences = (llama_seq_id *)p;
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}
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const std::vector<llama_kv_cell> & kv_cells = ctx->kv_self.cells;
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llama_kv_cache_view_cell * c_curr = view->cells;
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llama_seq_id * cs_curr = view->cells_sequences;
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int32_t used_cells = 0;
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int32_t token_count = 0;
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int32_t curr_contig_idx = -1;
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uint32_t max_contig = 0;
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int32_t max_contig_idx = -1;
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for (int32_t i = 0; i < int32_t(ctx->kv_self.size); i++, c_curr++, cs_curr += view->n_max_seq) {
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const size_t curr_size = kv_cells[i].seq_id.size();
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token_count += curr_size;
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c_curr->pos = kv_cells[i].pos + kv_cells[i].delta;
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if (curr_size > 0) {
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if (curr_contig_idx >= 0 && uint32_t(i - curr_contig_idx) > max_contig) {
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max_contig = i - curr_contig_idx;
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max_contig_idx = curr_contig_idx;
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}
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curr_contig_idx = -1;
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} else if (curr_contig_idx < 0) {
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curr_contig_idx = i;
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}
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int seq_idx = 0;
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for (const llama_seq_id it : kv_cells[i].seq_id) {
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if (seq_idx >= view->n_max_seq) {
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break;
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}
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cs_curr[seq_idx] = it;
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seq_idx++;
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}
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if (seq_idx != 0) {
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used_cells++;
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}
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for (; seq_idx < view->n_max_seq; seq_idx++) {
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cs_curr[seq_idx] = -1;
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}
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}
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if (curr_contig_idx >= 0 && kv_cells.size() - curr_contig_idx > max_contig) {
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max_contig_idx = curr_contig_idx;
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max_contig = kv_cells.size() - curr_contig_idx;
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}
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view->max_contiguous = max_contig;
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view->max_contiguous_idx = max_contig_idx;
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view->token_count = token_count;
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view->used_cells = used_cells;
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if (uint32_t(used_cells) != ctx->kv_self.used) {
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LLAMA_LOG_ERROR("%s: used cells mismatch. kv_cache says %d but we calculated %d\n",
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__func__, ctx->kv_self.used, used_cells);
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}
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}
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int llama_get_kv_cache_token_count(const struct llama_context * ctx) {
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int result = 0;
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48
llama.h
48
llama.h
@ -361,6 +361,54 @@ extern "C" {
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// KV cache
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//
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// Information associated with an individual cell in the KV cache view.
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struct llama_kv_cache_view_cell {
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// The position for this cell. Takes KV cache shifts into account.
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// May be negative if the cell is not populated.
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llama_pos pos;
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};
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// An updateable view of the KV cache.
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struct llama_kv_cache_view {
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// Number of KV cache cells. This will be the same as the context size.
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int32_t n_cells;
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// Maximum number of sequences that can exist in a cell. It's not an error
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// if there are more sequences in a cell than this value, however they will
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// not be visible in the view cells_sequences.
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int32_t n_max_seq;
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// Number of tokens in the cache. For example, if there are two populated
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// cells, the first with 1 sequence id in it and the second with 2 sequence
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// ids then you'll have 3 tokens.
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int32_t token_count;
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// Number of populated cache cells.
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int32_t used_cells;
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// Maximum contiguous empty slots in the cache.
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int32_t max_contiguous;
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// Index to the start of the max_contiguous slot range. Can be negative
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// when cache is full.
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int32_t max_contiguous_idx;
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// Information for an individual cell.
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struct llama_kv_cache_view_cell * cells;
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// The sequences for each cell. There will be n_max_seq items per cell.
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llama_seq_id * cells_sequences;
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};
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// Create an empty KV cache view.
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LLAMA_API struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_context * ctx, int32_t n_max_seq);
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// Free a KV cache view.
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LLAMA_API void llama_kv_cache_view_free(struct llama_kv_cache_view * view);
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// Update the KV cache view structure with the current state of the KV cache.
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LLAMA_API void llama_kv_cache_view_update(const struct llama_context * ctx, struct llama_kv_cache_view * view);
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// Returns the number of tokens in the KV cache (slow, use only for debug)
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// If a KV cell has multiple sequences assigned to it, it will be counted multiple times
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LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
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