de2ef53a4b
* kv-cache : rework kv_cell ggml-ci * kv-cells : use "shift" instead of "delta" consistently ggml-ci * llama : add llama_max_parallel_sequences() ggml-ci * kv-cells : update comments [no ci] * context : fail upon construction if sequences exceed max value ggml-ci * kv-cells : get_pos() -> pos_get() + comments ggml-ci * kv-cells : fix tracking of "used" cells ggml-ci
41 lines
1,013 B
C++
41 lines
1,013 B
C++
#pragma once
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#include "llama.h"
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#include <cstdint>
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#define LLAMA_MAX_PARALLEL_SEQUENCES 64
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struct llama_cparams {
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uint32_t n_ctx; // context size used during inference
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uint32_t n_batch;
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uint32_t n_ubatch;
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uint32_t n_seq_max;
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int n_threads; // number of threads to use for generation
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int n_threads_batch; // number of threads to use for batch processing
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float rope_freq_base;
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float rope_freq_scale;
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uint32_t n_ctx_orig_yarn;
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// These hyperparameters are not exposed in GGUF, because all
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// existing YaRN models use the same values for them.
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float yarn_ext_factor;
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float yarn_attn_factor;
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float yarn_beta_fast;
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float yarn_beta_slow;
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float defrag_thold;
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bool embeddings;
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bool causal_attn;
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bool offload_kqv;
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bool flash_attn;
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bool no_perf;
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bool warmup;
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bool op_offload;
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enum llama_pooling_type pooling_type;
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ggml_backend_sched_eval_callback cb_eval;
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void * cb_eval_user_data;
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};
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