From a867b919ca1e26cc828f98c35b4c6926e8e54762 Mon Sep 17 00:00:00 2001 From: Kawrakow Date: Sat, 21 Dec 2024 08:32:39 +0100 Subject: IQ2_XS_R4 (#155) * iq2_xs_r4: Zen4 * iq2_xs_r4: AVX2 * iq2_xs_r4: slightly better matrix x vector on AVX2 * iq2_xs_r4: NEON - not much better than iq2_xs * iq2_xs_r4: slightly better NEON --------- Co-authored-by: Iwan Kawrakow --- src/llama.cpp | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) (limited to 'src/llama.cpp') diff --git a/src/llama.cpp b/src/llama.cpp index df700c12..eac0d866 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -3852,6 +3852,7 @@ struct llama_model_loader { case GGML_TYPE_IQ2_XXS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XXS; break; case GGML_TYPE_IQ2_XXS_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4; break; case GGML_TYPE_IQ2_XS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_XS; break; + case GGML_TYPE_IQ2_XS_R4:ftype = LLAMA_FTYPE_MOSTLY_IQ2_XS_R4; break; case GGML_TYPE_IQ2_KS: ftype = LLAMA_FTYPE_MOSTLY_IQ2_KS; break; case GGML_TYPE_IQ2_S: ftype = LLAMA_FTYPE_MOSTLY_IQ2_S; break; case GGML_TYPE_IQ3_XXS: ftype = LLAMA_FTYPE_MOSTLY_IQ3_XXS; break; @@ -4581,6 +4582,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) { case LLAMA_FTYPE_MOSTLY_IQ2_XXS: return "IQ2_XXS - 2.0625 bpw"; case LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4:return "IQ2_XXS_R4 - 2.0625 bpw"; case LLAMA_FTYPE_MOSTLY_IQ2_XS: return "IQ2_XS - 2.3125 bpw"; + case LLAMA_FTYPE_MOSTLY_IQ2_XS_R4:return "IQ2_XS_R4 - 2.3125 bpw"; case LLAMA_FTYPE_MOSTLY_IQ2_KS: return "IQ2_KS - 2.1875 bpw"; case LLAMA_FTYPE_MOSTLY_IQ2_S: return "IQ2_S - 2.5 bpw"; case LLAMA_FTYPE_MOSTLY_IQ2_M: return "IQ2_M - 2.7 bpw"; @@ -15797,10 +15799,10 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M || ftype == LLAMA_FTYPE_MOSTLY_IQ2_K || ftype == LLAMA_FTYPE_MOSTLY_IQ3_K || ftype == LLAMA_FTYPE_MOSTLY_IQ2_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ3_K_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ2_K_R4 || - ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS_R4) { + ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS_R4) { new_type = !qs.has_output ? GGML_TYPE_IQ4_K : GGML_TYPE_Q5_K; } - else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4) { + else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS_R4) { new_type = !qs.has_output ? GGML_TYPE_IQ4_K_R4 : GGML_TYPE_Q5_K_R4; } else if ((ftype == LLAMA_FTYPE_MOSTLY_IQ3_S || ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS || @@ -15818,7 +15820,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n } else { if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M || - ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4) { + ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS_R4) { new_type = GGML_TYPE_Q2_K; } else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) { @@ -15894,7 +15896,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n } } else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ1_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M || ftype == LLAMA_FTYPE_MOSTLY_IQ1_M || - ftype == LLAMA_FTYPE_MOSTLY_IQ2_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4) { + ftype == LLAMA_FTYPE_MOSTLY_IQ2_KS || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ2_XS_R4) { if (name.find("attn_v.weight") != std::string::npos) { if (qs.model.hparams.n_gqa() >= 4 || qs.model.hparams.n_expert >= 4) new_type = GGML_TYPE_IQ4_K; else if (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2) new_type = GGML_TYPE_IQ3_K; @@ -16188,7 +16190,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n new_type == GGML_TYPE_Q5_K_R4 || new_type == GGML_TYPE_Q3_K_R4 || new_type == GGML_TYPE_Q2_K_R4 || new_type == GGML_TYPE_IQ4_K_R4|| new_type == GGML_TYPE_Q8_K_R8 || new_type == GGML_TYPE_IQ3_K_R4|| new_type == GGML_TYPE_IQ2_K_R4|| new_type == GGML_TYPE_IQ5_K_R4|| new_type == GGML_TYPE_IQ4_KS_R4 || - new_type == GGML_TYPE_IQ3_XXS_R4 || new_type == GGML_TYPE_IQ2_XXS_R4) { + new_type == GGML_TYPE_IQ3_XXS_R4 || new_type == GGML_TYPE_IQ2_XXS_R4 || new_type == GGML_TYPE_IQ2_XS_R4) { int nx = tensor->ne[0]; int ny = tensor->ne[1]; if (nx % QK_K != 0) { @@ -16209,6 +16211,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n case GGML_TYPE_IQ2_XXS: case GGML_TYPE_IQ2_XXS_R4: case GGML_TYPE_IQ2_XS: + case GGML_TYPE_IQ2_XS_R4: case GGML_TYPE_IQ2_KS: case GGML_TYPE_IQ2_S: case GGML_TYPE_IQ3_XXS: @@ -16341,6 +16344,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s case LLAMA_FTYPE_MOSTLY_IQ2_XXS: default_type = GGML_TYPE_IQ2_XXS; break; case LLAMA_FTYPE_MOSTLY_IQ2_XXS_R4:default_type = GGML_TYPE_IQ2_XXS_R4; break; case LLAMA_FTYPE_MOSTLY_IQ2_XS: default_type = GGML_TYPE_IQ2_XS; break; + case LLAMA_FTYPE_MOSTLY_IQ2_XS_R4:default_type = GGML_TYPE_IQ2_XS_R4; break; case LLAMA_FTYPE_MOSTLY_IQ2_KS: default_type = GGML_TYPE_IQ2_KS; break; case LLAMA_FTYPE_MOSTLY_IQ2_S: default_type = GGML_TYPE_IQ2_XS; break; case LLAMA_FTYPE_MOSTLY_IQ2_M: default_type = GGML_TYPE_IQ2_S; break; @@ -16695,6 +16699,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s (new_type == GGML_TYPE_IQ2_XXS || new_type == GGML_TYPE_IQ2_XXS_R4 || new_type == GGML_TYPE_IQ2_XS || + new_type == GGML_TYPE_IQ2_XS_R4 || new_type == GGML_TYPE_IQ2_S || new_type == GGML_TYPE_IQ1_S || (new_type == GGML_TYPE_IQ1_M && strcmp(tensor->name, "token_embd.weight") && strcmp(tensor->name, "output.weight")) || @@ -16800,6 +16805,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ2_XXS; else chunk_size_multiplier = 4; } + else if (new_type == GGML_TYPE_IQ2_XS_R4) { + if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ2_XS; + else chunk_size_multiplier = 4; + } else if (new_type == GGML_TYPE_IQ3_XXS_R4) { if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_IQ3_XXS; else chunk_size_multiplier = 4; -- cgit v1.2.3