From ce711f6eae1079592e060e47ec23b6a795387ce6 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Mon, 1 Jul 2024 18:26:24 +0300 Subject: [PATCH] llama : minor styling --- src/llama.cpp | 89 +++++++++++++++++++++++++++------------------------ 1 file changed, 48 insertions(+), 41 deletions(-) diff --git a/src/llama.cpp b/src/llama.cpp index 1f6763573..eea532f6a 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -2087,6 +2087,7 @@ struct llama_hparams { uint32_t n_head_kv; uint32_t n_layer; uint32_t n_rot; + uint32_t n_swa = 0; // sliding window attention (SWA) uint32_t n_embd_head_k; // dimension of keys (d_k). d_q is assumed to be the same, but there are n_head q heads, and only n_head_kv k-v heads uint32_t n_embd_head_v; // dimension of values (d_v) aka n_embd_head uint32_t n_ff; @@ -2101,7 +2102,6 @@ struct llama_hparams { uint32_t n_ff_shexp = 0; uint32_t n_expert_shared = 0; float expert_weights_scale = 0.0; - uint32_t n_swa = 0; // sliding window attention (SWA) float f_norm_eps; float f_norm_rms_eps; @@ -2142,6 +2142,7 @@ struct llama_hparams { if (this->n_head_kv != other.n_head_kv) return true; if (this->n_layer != other.n_layer) return true; if (this->n_rot != other.n_rot) return true; + if (this->n_swa != other.n_swa) return true; if (this->n_embd_head_k != other.n_embd_head_k) return true; if (this->n_embd_head_v != other.n_embd_head_v) return true; if (this->n_ff != other.n_ff) return true; @@ -2652,20 +2653,18 @@ struct llama_context { void * abort_callback_data = nullptr; // input tensors - struct ggml_tensor * inp_tokens; // I32 [n_batch] - struct ggml_tensor * inp_embd; // F32 [n_embd, n_batch] - struct ggml_tensor * inp_pos; // I32 [n_batch] - struct ggml_tensor * inp_out_ids; // I32 [n_outputs] - struct ggml_tensor * inp_KQ_mask; // F32 [kv_size, n_batch] - struct ggml_tensor * inp_K_shift; // I32 [kv_size] - struct ggml_tensor * inp_mean; // F32 [n_batch, n_batch] - struct ggml_tensor * inp_cls; // I32 [n_batch] - struct ggml_tensor * inp_s_copy; // I32 [kv_size] - struct ggml_tensor * inp_s_mask; // F32 [1, n_kv] - struct ggml_tensor * inp_s_seq; // I32 [n_kv, n_batch] - - // KQ mask per layer, used by sliding window attention (gemma 2) - struct ggml_tensor * inp_KQ_mask_swa; + struct ggml_tensor * inp_tokens; // I32 [n_batch] + struct ggml_tensor * inp_embd; // F32 [n_embd, n_batch] + struct ggml_tensor * inp_pos; // I32 [n_batch] + struct ggml_tensor * inp_out_ids; // I32 [n_outputs] + struct ggml_tensor * inp_KQ_mask; // F32 [kv_size, n_batch] + struct ggml_tensor * inp_KQ_mask_swa; // F32 [kv_size, n_batch] + struct ggml_tensor * inp_K_shift; // I32 [kv_size] + struct ggml_tensor * inp_mean; // F32 [n_batch, n_batch] + struct ggml_tensor * inp_cls; // I32 [n_batch] + struct ggml_tensor * inp_s_copy; // I32 [kv_size] + struct ggml_tensor * inp_s_mask; // F32 [1, n_kv] + struct ggml_tensor * inp_s_seq; // I32 [n_kv, n_batch] // control vectors struct llama_control_vector cvec; @@ -5427,6 +5426,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) { LLAMA_LOG_INFO("%s: n_head_kv = %u\n", __func__, hparams.n_head_kv); LLAMA_LOG_INFO("%s: n_layer = %u\n", __func__, hparams.n_layer); LLAMA_LOG_INFO("%s: n_rot = %u\n", __func__, hparams.n_rot); + LLAMA_LOG_INFO("%s: n_swa = %u\n", __func__, hparams.n_swa); LLAMA_LOG_INFO("%s: n_embd_head_k = %u\n", __func__, hparams.n_embd_head_k); LLAMA_LOG_INFO("%s: n_embd_head_v = %u\n", __func__, hparams.n_embd_head_v); LLAMA_LOG_INFO("%s: n_gqa = %u\n", __func__, hparams.n_gqa()); @@ -7783,18 +7783,18 @@ struct llm_build_context { ctx0 = ggml_init(params); - lctx.inp_tokens = nullptr; - lctx.inp_embd = nullptr; - lctx.inp_pos = nullptr; - lctx.inp_out_ids = nullptr; - lctx.inp_KQ_mask = nullptr; - lctx.inp_K_shift = nullptr; - lctx.inp_mean = nullptr; - lctx.inp_cls = nullptr; - lctx.inp_s_copy = nullptr; - lctx.inp_s_mask = nullptr; - lctx.inp_s_seq = nullptr; + lctx.inp_tokens = nullptr; + lctx.inp_embd = nullptr; + lctx.inp_pos = nullptr; + lctx.inp_out_ids = nullptr; + lctx.inp_KQ_mask = nullptr; lctx.inp_KQ_mask_swa = nullptr; + lctx.inp_K_shift = nullptr; + lctx.inp_mean = nullptr; + lctx.inp_cls = nullptr; + lctx.inp_s_copy = nullptr; + lctx.inp_s_mask = nullptr; + lctx.inp_s_seq = nullptr; } void free() { @@ -7813,7 +7813,6 @@ struct llm_build_context { cb(lctx.inp_K_shift, "K_shift", -1); ggml_set_input(lctx.inp_K_shift); - for (int il = 0; il < n_layer; ++il) { struct ggml_tensor * rope_factors = build_rope_factors(il); struct ggml_tensor * tmp = @@ -7947,18 +7946,26 @@ struct llm_build_context { return lctx.inp_out_ids; } - struct ggml_tensor * build_inp_KQ_mask(bool causal = true, bool sliding_window = false) { - struct ggml_tensor * KQ_mask = causal + struct ggml_tensor * build_inp_KQ_mask(bool causal = true) { + lctx.inp_KQ_mask = causal ? ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_kv, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD)) : ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD)); - cb(KQ_mask, "KQ_mask", -1); - ggml_set_input(KQ_mask); - if (sliding_window) { - lctx.inp_KQ_mask_swa = KQ_mask; - } else { - lctx.inp_KQ_mask = KQ_mask; - } - return flash_attn ? ggml_cast(ctx0, KQ_mask, GGML_TYPE_F16) : KQ_mask; + cb(lctx.inp_KQ_mask, "KQ_mask", -1); + ggml_set_input(lctx.inp_KQ_mask); + + return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_mask, GGML_TYPE_F16) : lctx.inp_KQ_mask; + } + + struct ggml_tensor * build_inp_KQ_mask_swa(bool causal = true) { + GGML_ASSERT(hparams.n_swa > 0); + + lctx.inp_KQ_mask_swa = causal + ? ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_kv, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD)) + : ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, GGML_PAD(n_tokens, GGML_KQ_MASK_PAD)); + cb(lctx.inp_KQ_mask_swa, "KQ_mask_swa", -1); + ggml_set_input(lctx.inp_KQ_mask_swa); + + return flash_attn ? ggml_cast(ctx0, lctx.inp_KQ_mask_swa, GGML_TYPE_F16) : lctx.inp_KQ_mask_swa; } struct ggml_tensor * build_inp_mean() { @@ -11042,12 +11049,12 @@ struct llm_build_context { // KQ_mask (mask for 1 head, it will be broadcasted to all heads) // gemma 2 requires different mask for layers using sliding window (SWA) - struct ggml_tensor * KQ_mask_full = build_inp_KQ_mask(true, false); - struct ggml_tensor * KQ_mask_SWA = build_inp_KQ_mask(true, true); + struct ggml_tensor * KQ_mask = build_inp_KQ_mask(true); + struct ggml_tensor * KQ_mask_swa = build_inp_KQ_mask_swa(true); for (int il = 0; il < n_layer; ++il) { // (il % 2) layers use SWA - struct ggml_tensor * KQ_mask = (il % 2 == 0) ? KQ_mask_SWA : KQ_mask_full; + struct ggml_tensor * KQ_mask_l = (il % 2 == 0) ? KQ_mask_swa : KQ_mask; // norm cur = llm_build_norm(ctx0, inpL, hparams, @@ -11084,7 +11091,7 @@ struct llm_build_context { cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf, model.layers[il].wo, NULL, - Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il); + Kcur, Vcur, Qcur, KQ_mask_l, n_tokens, kv_head, n_kv, 1.0f, cb, il); } cur = llm_build_norm(ctx0, cur, hparams,