debug log

Author: orca-zhang

src/llama-model.cpp

@@ -2946,29 +2946,30 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                                 buft = ggml_backend_dev_buffer_type(cpu_dev);
                             }
 
+                            LLAMA_LOG_INFO("n_head_kv: %d, kv_lora_rank: %d, n_embd_head_qk_nope: %d\n", n_head_kv, kv_lora_rank, n_embd_head_qk_nope);
                             ggml_context * ctx = ctx_for_buft(buft);
                             layer.wk_b = ggml_new_tensor_2d(ctx,
                                 wkv_b->type,
                                 n_head_kv * kv_lora_rank,
                                 n_embd_head_qk_nope
                             );
-                            LLAMA_LOG_DEBUG("111\n", 0);
+                            LLAMA_LOG_INFO("wk_b shape: [%d, %d]\n", layer.wk_b->ne[0], layer.wk_b->ne[1]);
                             {
                                 float *src = (float *)wkv_b->data;
                                 float *dst = (float *)layer.wk_b->data;
                                 int src_stride = wkv_b->ne[0]; // 原始张量每行的元素数
 
-                                LLAMA_LOG_DEBUG("222\n", 0);
                                 for (int h = 0; h < n_head_kv; ++h) {
                                     int k_start = h * (n_embd_head_qk_nope + n_embd_head_v);
                                     for (int row = 0; row < kv_lora_rank; ++row) {
                                         for (int col = 0; col < n_embd_head_qk_nope; ++col) {
-                                            LLAMA_LOG_DEBUG("333 row: %d, col: %d\n", row, col);
+                                            LLAMA_LOG_INFO("wk_b row: %d, col: %d\n", row, col);
                                             int src_idx = row * src_stride + k_start + col;
                                             GGML_ASSERT(src_idx < ggml_nelements(wkv_b));
 
                                             int dst_row = h * kv_lora_rank + row;
                                             int dst_col = col;
+                                            LLAMA_LOG_INFO("wk_b dst_row: %d, dst_col: %d\n", dst_row, dst_col);
                                             dst[dst_row * n_embd_head_qk_nope + dst_col] = src[src_idx];
                                         }
                                     }
@@ -2981,25 +2982,25 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                                 n_head_kv * n_embd_head_v,  // 行数：合并头和特征维度
                                 kv_lora_rank                // 列数：LoRA 秩
                             );
-                            LLAMA_LOG_DEBUG("444\n", 0);
+                            LLAMA_LOG_INFO("wv_b shape: [%d, %d]\n", layer.wv_b->ne[0], layer.wv_b->ne[1]);
                             {
                                 float *src = (float *)wkv_b->data;
                                 float *dst = (float *)layer.wv_b->data;
                                 int src_stride = wkv_b->ne[0]; // 原始张量每行的元素数
 
-                                LLAMA_LOG_DEBUG("555\n", 0);
                                 for (int h = 0; h < n_head_kv; ++h) {
                                     int v_start = h * (n_embd_head_qk_nope + n_embd_head_v) + n_embd_head_qk_nope;
                                     for (int row = 0; row < kv_lora_rank; ++row) {
                                         for (int col = 0; col < n_embd_head_v; ++col) {
-                                            LLAMA_LOG_DEBUG("666 row: %d, col: %d\n", row, col);
+                                            LLAMA_LOG_INFO("wv_b row: %d, col: %d\n", row, col);
                                             // 源索引计算
                                             int src_idx = row * src_stride + v_start + col;
                                             GGML_ASSERT(src_idx < ggml_nelements(wkv_b));
 
                                             // 目标索引计算
                                             int dst_row = h * n_embd_head_v + col; // 合并头和特征维度
                                             int dst_col = row;                     // LoRA 秩维度
+                                            LLAMA_LOG_INFO("wv_b dst_row: %d, dst_col: %d\n", dst_row, dst_col);
                                             dst[dst_row * kv_lora_rank + dst_col] = src[src_idx];
                                         }
                                     }