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llama : fix sanity checks during quantization #17721

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ggerganov merged 1 commit into from
Dec 4, 2025
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llama : fix sanity checks during quantization #17721

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12 changes: 5 additions & 7 deletions src/llama-quant.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -726,21 +726,19 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
// sanity checks for models that have attention layers
if (qs.n_attention_wv != 0 && !is_clip_model)
{
const auto & n_head_kv_iter = model.hparams.n_head_kv_arr.begin();
// attention layers have a non-zero number of kv heads
int32_t n_layer_attn = model.hparams.n_layer - std::count(n_head_kv_iter, n_head_kv_iter + model.hparams.n_layer, 0);
int32_t n_layer_all = model.hparams.n_layer;
if (llama_model_has_encoder(&model)) {
// now n_layer_attn is the number of attention layers in the encoder
// now n_layer_all is the number of attention layers in the encoder
// for each decoder block, there are 2 attention layers
n_layer_attn += 2 * model.hparams.dec_n_layer;
n_layer_all += 2 * model.hparams.dec_n_layer;
}

// note: for linear-attention models (such as Qwen3 Next) this is the number of linear layers
const int32_t n_layer_recr = std::count(model.hparams.recurrent_layer_arr.begin(), model.hparams.recurrent_layer_arr.end(), true);

LLAMA_LOG_INFO("%s: n_layer_attn = %d, n_layer_recr = %d, pruned_attention_w = %d\n", __func__, n_layer_attn, n_layer_recr, pruned_attention_w);
LLAMA_LOG_INFO("%s: n_layer_all = %d, n_layer_recr = %d, pruned_attention_w = %d\n", __func__, n_layer_all, n_layer_recr, pruned_attention_w);

GGML_ASSERT((qs.n_attention_wv == n_layer_attn - pruned_attention_w - n_layer_recr) && "n_attention_wv is unexpected");
GGML_ASSERT((qs.n_attention_wv == n_layer_all - pruned_attention_w - n_layer_recr) && "n_attention_wv is unexpected");
}

size_t total_size_org = 0;
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