File size: 1,884 Bytes
8efb28e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | #pragma once
#include "llama.h"
#include <cstdint>
#include <vector>
#define LLAMA_MAX_SEQ 256
struct llama_cparams {
uint32_t n_ctx; // context size used during inference
uint32_t n_ctx_seq; // context for a single sequence
uint32_t n_batch;
uint32_t n_ubatch;
uint32_t n_seq_max;
uint32_t n_rs_seq; // number of recurrent-state snapshots per seq for rollback
uint32_t n_outputs_max; // max outputs supported by the context
int32_t n_threads; // number of threads to use for generation
int32_t n_threads_batch; // number of threads to use for batch processing
int32_t nextn_layer_offset = 0;
float rope_freq_base;
float rope_freq_scale;
uint32_t n_ctx_orig_yarn;
// These hyperparameters are not exposed in GGUF, because all
// existing YaRN models use the same values for them.
float yarn_ext_factor;
float yarn_attn_factor;
float yarn_beta_fast;
float yarn_beta_slow;
bool embeddings;
bool embeddings_nextn; // also extract the hidden state before the final output norm
bool embeddings_nextn_masked; // extract for only rows where batch.logits != 0
bool causal_attn;
bool offload_kqv;
bool flash_attn;
bool auto_fa;
bool fused_gdn_ar; // use fused gated delta net (autoregressive)
bool fused_gdn_ch; // use fused gated delta net (chunked)
bool auto_fgdn;
bool no_perf;
bool warmup; // TODO: remove [TAG_LLAMA_GRAPH_NO_WARMUP]
bool op_offload;
bool kv_unified;
bool pipeline_parallel;
std::vector<bool> embeddings_layer_inp; // [n_layer()] extract input embeddings for layer
enum llama_context_type ctx_type;
enum llama_pooling_type pooling_type;
ggml_backend_sched_eval_callback cb_eval;
void * cb_eval_user_data;
llama_context * ctx_other;
};
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