fix: GLM-DSA crash in llama-tokenize when using vocab_only (#22102)

* llama: fix crash in print_info for GLM-DSA when vocab_only is set

* addressed code review comments

* cont : simplify

---------

Co-authored-by: Georgi Gerganov <redacted>

diff --git a/src/llama-model.cpp b/src/llama-model.cpp
index 4ded484dd1cba787232d8c8e6beb2d68ce151479..5f543e762c3b46075470eaa6029ab3714ec4520b 100644 (file)
--- a/src/llama-model.cpp
+++ b/src/llama-model.cpp
@@ -8180,114 +8180,114 @@ void llama_model::print_info() const {
             LLAMA_LOG_INFO("%s: n_cls_out             = %u\n", __func__, hparams.n_cls_out);
 
             size_t i = 0;
-            for (auto label : classifier_labels) {
+            for (const auto & label : classifier_labels) {
                 LLAMA_LOG_INFO("%s: cls_label[%2zu]         = %s\n", __func__, i++, label.c_str());
             }
         }
-    }
 
-    if (arch == LLM_ARCH_MAMBA ||
-        arch == LLM_ARCH_MAMBA2 ||
-        arch == LLM_ARCH_JAMBA ||
-        arch == LLM_ARCH_FALCON_H1 ||
-        arch == LLM_ARCH_PLAMO2 ||
-        arch == LLM_ARCH_GRANITE_HYBRID ||
-        arch == LLM_ARCH_QWEN3NEXT ||
-        arch == LLM_ARCH_QWEN35 ||
-        arch == LLM_ARCH_QWEN35MOE ||
-        arch == LLM_ARCH_NEMOTRON_H ||
-        arch == LLM_ARCH_NEMOTRON_H_MOE) {
-        LLAMA_LOG_INFO("%s: ssm_d_conv            = %u\n",     __func__, hparams.ssm_d_conv);
-        LLAMA_LOG_INFO("%s: ssm_d_inner           = %u\n",     __func__, hparams.ssm_d_inner);
-        LLAMA_LOG_INFO("%s: ssm_d_state           = %u\n",     __func__, hparams.ssm_d_state);
-        LLAMA_LOG_INFO("%s: ssm_dt_rank           = %u\n",     __func__, hparams.ssm_dt_rank);
-        LLAMA_LOG_INFO("%s: ssm_n_group           = %u\n",     __func__, hparams.ssm_n_group);
-        LLAMA_LOG_INFO("%s: ssm_dt_b_c_rms        = %d\n",     __func__, hparams.ssm_dt_b_c_rms);
-    }
+        if (arch == LLM_ARCH_MAMBA ||
+                arch == LLM_ARCH_MAMBA2 ||
+                arch == LLM_ARCH_JAMBA ||
+                arch == LLM_ARCH_FALCON_H1 ||
+                arch == LLM_ARCH_PLAMO2 ||
+                arch == LLM_ARCH_GRANITE_HYBRID ||
+                arch == LLM_ARCH_QWEN3NEXT ||
+                arch == LLM_ARCH_QWEN35 ||
+                arch == LLM_ARCH_QWEN35MOE ||
+                arch == LLM_ARCH_NEMOTRON_H ||
+                arch == LLM_ARCH_NEMOTRON_H_MOE) {
+            LLAMA_LOG_INFO("%s: ssm_d_conv            = %u\n",     __func__, hparams.ssm_d_conv);
+            LLAMA_LOG_INFO("%s: ssm_d_inner           = %u\n",     __func__, hparams.ssm_d_inner);
+            LLAMA_LOG_INFO("%s: ssm_d_state           = %u\n",     __func__, hparams.ssm_d_state);
+            LLAMA_LOG_INFO("%s: ssm_dt_rank           = %u\n",     __func__, hparams.ssm_dt_rank);
+            LLAMA_LOG_INFO("%s: ssm_n_group           = %u\n",     __func__, hparams.ssm_n_group);
+            LLAMA_LOG_INFO("%s: ssm_dt_b_c_rms        = %d\n",     __func__, hparams.ssm_dt_b_c_rms);
+        }
 
-    LLAMA_LOG_INFO("%s: model type            = %s\n",     __func__, type_name().c_str());
-    if (pimpl->n_elements >= 1e12) {
-        LLAMA_LOG_INFO("%s: model params          = %.2f T\n", __func__, pimpl->n_elements*1e-12);
-    } else if (pimpl->n_elements >= 1e9) {
-        LLAMA_LOG_INFO("%s: model params          = %.2f B\n", __func__, pimpl->n_elements*1e-9);
-    } else if (pimpl->n_elements >= 1e6) {
-        LLAMA_LOG_INFO("%s: model params          = %.2f M\n", __func__, pimpl->n_elements*1e-6);
-    } else {
-        LLAMA_LOG_INFO("%s: model params          = %.2f K\n", __func__, pimpl->n_elements*1e-3);
-    }
+        LLAMA_LOG_INFO("%s: model type            = %s\n",     __func__, type_name().c_str());
+        if (pimpl->n_elements >= 1e12) {
+            LLAMA_LOG_INFO("%s: model params          = %.2f T\n", __func__, pimpl->n_elements*1e-12);
+        } else if (pimpl->n_elements >= 1e9) {
+            LLAMA_LOG_INFO("%s: model params          = %.2f B\n", __func__, pimpl->n_elements*1e-9);
+        } else if (pimpl->n_elements >= 1e6) {
+            LLAMA_LOG_INFO("%s: model params          = %.2f M\n", __func__, pimpl->n_elements*1e-6);
+        } else {
+            LLAMA_LOG_INFO("%s: model params          = %.2f K\n", __func__, pimpl->n_elements*1e-3);
+        }
 
-    // general kv
-    LLAMA_LOG_INFO("%s: general.name          = %s\n",    __func__, name.c_str());
+        // general kv
+        LLAMA_LOG_INFO("%s: general.name          = %s\n",    __func__, name.c_str());
 
-    if (arch == LLM_ARCH_DEEPSEEK) {
-        LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
-        LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
-    }
+        if (arch == LLM_ARCH_DEEPSEEK) {
+            LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
+            LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
+        }
 
-    if (arch == LLM_ARCH_DEEPSEEK2 || arch == LLM_ARCH_DEEPSEEK2OCR || arch == LLM_ARCH_GLM_DSA || arch == LLM_ARCH_MISTRAL4) {
-        LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
-        LLAMA_LOG_INFO("%s: n_lora_q              = %d\n",     __func__, hparams.n_lora_q);
-        LLAMA_LOG_INFO("%s: n_lora_kv             = %d\n",     __func__, hparams.n_lora_kv);
-        LLAMA_LOG_INFO("%s: n_embd_head_k_mla     = %d\n",     __func__, hparams.n_embd_head_k_mla());
-        LLAMA_LOG_INFO("%s: n_embd_head_v_mla     = %d\n",     __func__, hparams.n_embd_head_v_mla());
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
-        LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
-        LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
-        LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
-    }
+        if (arch == LLM_ARCH_DEEPSEEK2 || arch == LLM_ARCH_DEEPSEEK2OCR || arch == LLM_ARCH_GLM_DSA || arch == LLM_ARCH_MISTRAL4) {
+            LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
+            LLAMA_LOG_INFO("%s: n_lora_q              = %d\n",     __func__, hparams.n_lora_q);
+            LLAMA_LOG_INFO("%s: n_lora_kv             = %d\n",     __func__, hparams.n_lora_kv);
+            LLAMA_LOG_INFO("%s: n_embd_head_k_mla     = %d\n",     __func__, hparams.n_embd_head_k_mla());
+            LLAMA_LOG_INFO("%s: n_embd_head_v_mla     = %d\n",     __func__, hparams.n_embd_head_v_mla());
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
+            LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
+            LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
+            LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
+        }
 
-    if (arch == LLM_ARCH_QWEN2MOE) {
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n",     __func__, hparams.n_ff_shexp);
-    }
+        if (arch == LLM_ARCH_QWEN2MOE) {
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n",     __func__, hparams.n_ff_shexp);
+        }
 
-    if (arch == LLM_ARCH_QWEN3MOE || arch == LLM_ARCH_OPENAI_MOE || arch == LLM_ARCH_QWEN3VLMOE || arch == LLM_ARCH_RND1) {
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-    }
+        if (arch == LLM_ARCH_QWEN3MOE || arch == LLM_ARCH_OPENAI_MOE || arch == LLM_ARCH_QWEN3VLMOE || arch == LLM_ARCH_RND1) {
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+        }
 
-    if (arch == LLM_ARCH_MINICPM ||
-        arch == LLM_ARCH_GRANITE ||
-        arch == LLM_ARCH_GRANITE_MOE ||
-        arch == LLM_ARCH_GRANITE_HYBRID ||
-        arch == LLM_ARCH_NEMOTRON_H_MOE) {
-        LLAMA_LOG_INFO("%s: f_embedding_scale     = %f\n", __func__, hparams.f_embedding_scale);
-        LLAMA_LOG_INFO("%s: f_residual_scale      = %f\n", __func__, hparams.f_residual_scale);
-        LLAMA_LOG_INFO("%s: f_attention_scale     = %f\n", __func__, hparams.f_attention_scale);
-        LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n", __func__, hparams.n_ff_shexp);
-    }
+        if (arch == LLM_ARCH_MINICPM ||
+                arch == LLM_ARCH_GRANITE ||
+                arch == LLM_ARCH_GRANITE_MOE ||
+                arch == LLM_ARCH_GRANITE_HYBRID ||
+                arch == LLM_ARCH_NEMOTRON_H_MOE) {
+            LLAMA_LOG_INFO("%s: f_embedding_scale     = %f\n", __func__, hparams.f_embedding_scale);
+            LLAMA_LOG_INFO("%s: f_residual_scale      = %f\n", __func__, hparams.f_residual_scale);
+            LLAMA_LOG_INFO("%s: f_attention_scale     = %f\n", __func__, hparams.f_attention_scale);
+            LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n", __func__, hparams.n_ff_shexp);
+        }
 
-    if (arch == LLM_ARCH_BAILINGMOE) {
-        LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
-        LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
-        LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
-    }
+        if (arch == LLM_ARCH_BAILINGMOE) {
+            LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
+            LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
+            LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
+        }
 
-    if (arch == LLM_ARCH_BAILINGMOE2) {
-        LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n",     __func__, hparams.n_ff_shexp);
-        LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
-        LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
-        LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
-        LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
-        LLAMA_LOG_INFO("%s: nextn_predict_layers  = %d\n",     __func__, hparams.nextn_predict_layers);
-    }
+        if (arch == LLM_ARCH_BAILINGMOE2) {
+            LLAMA_LOG_INFO("%s: n_layer_dense_lead    = %d\n",     __func__, hparams.n_layer_dense_lead);
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_ff_shexp            = %d\n",     __func__, hparams.n_ff_shexp);
+            LLAMA_LOG_INFO("%s: n_expert_shared       = %d\n",     __func__, hparams.n_expert_shared);
+            LLAMA_LOG_INFO("%s: expert_weights_scale  = %.1f\n",   __func__, hparams.expert_weights_scale);
+            LLAMA_LOG_INFO("%s: expert_weights_norm   = %d\n",     __func__, hparams.expert_weights_norm);
+            LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
+            LLAMA_LOG_INFO("%s: nextn_predict_layers  = %d\n",     __func__, hparams.nextn_predict_layers);
+        }
 
-    if (arch == LLM_ARCH_SMALLTHINKER || arch == LLM_ARCH_LFM2MOE) {
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
-    }
+        if (arch == LLM_ARCH_SMALLTHINKER || arch == LLM_ARCH_LFM2MOE) {
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: expert_gating_func    = %s\n",     __func__, llama_expert_gating_func_name((llama_expert_gating_func_type) hparams.expert_gating_func));
+        }
 
-    if (arch == LLM_ARCH_GROVEMOE) {
-        LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
-        LLAMA_LOG_INFO("%s: n_ff_chexp            = %d\n",     __func__, hparams.n_ff_chexp);
-        LLAMA_LOG_INFO("%s: n_group_experts       = %d\n",     __func__, hparams.n_group_experts);
-        LLAMA_LOG_INFO("%s: expert_group_scale    = %.2f\n",   __func__, hparams.expert_group_scale);
+        if (arch == LLM_ARCH_GROVEMOE) {
+            LLAMA_LOG_INFO("%s: n_ff_exp              = %d\n",     __func__, hparams.n_ff_exp);
+            LLAMA_LOG_INFO("%s: n_ff_chexp            = %d\n",     __func__, hparams.n_ff_chexp);
+            LLAMA_LOG_INFO("%s: n_group_experts       = %d\n",     __func__, hparams.n_group_experts);
+            LLAMA_LOG_INFO("%s: expert_group_scale    = %.2f\n",   __func__, hparams.expert_group_scale);
+        }
     }
 
     vocab.print_info();