mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-11-15 11:17:31 +00:00
cd5e3b5754
* server : support unified context across slots * cont : fix speculative decoding initialization * context : fix n_ctx_per_seq computation * server : purge slots one by one * tests : add unified cache server tests * llama : update per-seq context computation * test-thread-safety : handle tiny training context of the input model * server : fix server_tokens clear() * server : use 4 slots + unified KV by default * llama : add note about context size queries * cont : update todos [no ci] * context : do not cap the size of the context * tests : adjust parameters to be CI friendlier * context : add warning
43 lines
1.0 KiB
C++
43 lines
1.0 KiB
C++
#pragma once
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#include "llama.h"
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#include <cstdint>
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#define LLAMA_MAX_SEQ 256
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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_ctx_seq; // context for a single sequence
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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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int32_t n_threads; // number of threads to use for generation
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int32_t 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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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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bool kv_unified;
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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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