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* kv-cache : prepare K/V buffers for separation ggml-ci * batched-bench : fix oob write ggml-ci * llama : add "virtual sequences" ggml-ci * llama : use "stream" vs "virtual sequence" ggml-ci * graph : fix stream splitting when KV cache is not used ggml-ci * kv-cache : add multi-stream save/load support ggml-ci * llama : add "--attn-streams" flag ggml-ci * kv-cache : fix handling when find_slot fails ggml-ci * kv-cache : restore find_slot impl ggml-ci * kv-cache : add comments * kv-cache : add bounds checks for sequence id ggml-ci * cont : add n_seq_max to batch allocr ggml-ci * kv-cache : perform stream copies lazily after llama_synchronize ggml-ci * kv-cache : avoid throwing exceptions across the C boundary ggml-ci * CUDA: 4D FlashAttention support (#14628) * CUDA: 4D FlashAttention support * CUDA: fix WMMA FA kernel * llama : rename attn_streams -> kv_unified ggml-ci * common : rename kv_split -> kv_unified ggml-ci --------- Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
43 lines
1019 B
C++
43 lines
1019 B
C++
#pragma once
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#include "llama.h"
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#include <cstdint>
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#define LLAMA_MAX_SEQ 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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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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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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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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