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llama : less KV padding when FA is off (#7257)

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ggml-ci
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Georgi Gerganov 2024-05-13 17:15:15 +03:00 committed by GitHub
parent 30e70334f7
commit 614d3b914e
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1 changed files with 13 additions and 7 deletions
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llama.cpp
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@ -2805,6 +2805,11 @@ static void llama_kv_cache_defrag(struct llama_kv_cache & cache) {
cache.do_defrag = true; cache.do_defrag = true;
} }
static uint32_t llama_kv_cache_get_padding(const struct llama_cparams & cparams) {
// the FA kernels require padding to avoid extra runtime boundary checks
return cparams.flash_attn ? 256u : 32u;
}
// //
// model loading and saving // model loading and saving
// //
@ -11510,7 +11515,8 @@ static int llama_decode_internal(
// a heuristic, to avoid attending the full cache if it is not yet utilized // a heuristic, to avoid attending the full cache if it is not yet utilized
// after enough generations, the benefit from this heuristic disappears // after enough generations, the benefit from this heuristic disappears
// if we start defragmenting the cache, the benefit from this will be more important // if we start defragmenting the cache, the benefit from this will be more important
kv_self.n = std::min(kv_self.size, std::max(256u, GGML_PAD(llama_kv_cache_cell_max(kv_self), 256))); const uint32_t pad = llama_kv_cache_get_padding(cparams);
kv_self.n = std::min(kv_self.size, std::max(pad, GGML_PAD(llama_kv_cache_cell_max(kv_self), pad)));
//kv_self.n = llama_kv_cache_cell_max(kv_self); //kv_self.n = llama_kv_cache_cell_max(kv_self);
} }
} }
@ -15511,6 +15517,11 @@ struct llama_context * llama_new_context_with_model(
return nullptr; return nullptr;
} }
if (params.flash_attn && model->arch == LLM_ARCH_GROK) {
LLAMA_LOG_WARN("%s: flash_attn is not compatible with Grok - forcing off\n", __func__);
params.flash_attn = false;
}
llama_context * ctx = new llama_context(*model); llama_context * ctx = new llama_context(*model);
const auto & hparams = model->hparams; const auto & hparams = model->hparams;
@ -15534,7 +15545,7 @@ struct llama_context * llama_new_context_with_model(
cparams.rope_freq_scale = params.rope_freq_scale == 0.0f ? hparams.rope_freq_scale_train : params.rope_freq_scale; cparams.rope_freq_scale = params.rope_freq_scale == 0.0f ? hparams.rope_freq_scale_train : params.rope_freq_scale;
// this is necessary due to kv_self.n being padded later during inference // this is necessary due to kv_self.n being padded later during inference
cparams.n_ctx = GGML_PAD(cparams.n_ctx, 256); cparams.n_ctx = GGML_PAD(cparams.n_ctx, llama_kv_cache_get_padding(cparams));
// with causal attention, the batch size is limited by the context size // with causal attention, the batch size is limited by the context size
cparams.n_batch = hparams.causal_attn ? std::min(cparams.n_ctx, params.n_batch) : params.n_batch; cparams.n_batch = hparams.causal_attn ? std::min(cparams.n_ctx, params.n_batch) : params.n_batch;
@ -15579,11 +15590,6 @@ struct llama_context * llama_new_context_with_model(
} }
} }
if (cparams.flash_attn && model->arch == LLM_ARCH_GROK) {
LLAMA_LOG_WARN("%s: flash_attn is not compatible with Grok - forcing off\n", __func__);
cparams.flash_attn = false;
}
if (params.seed == LLAMA_DEFAULT_SEED) { if (params.seed == LLAMA_DEFAULT_SEED) {
params.seed = time(NULL); params.seed = time(NULL);
} }