remove commented-out code blocks

Author: HimariO

examples/llava/clip.cpp

@@ -1042,9 +1042,6 @@ static ggml_cgraph * clip_image_build_graph_legacy(clip_ctx * ctx, const clip_im
                 KQ = ggml_soft_max_inplace(ctx0, KQ);
             } else {
                 KQ = ggml_soft_max_ext(ctx0, KQ, window_mask, 1.0f, 0.0f);
-                // KQ = ggml_scale_inplace(ctx0, KQ, 1.0f / sqrt((float)d_head));
-                // KQ = ggml_add(ctx0, KQ, window_mask);
-                // KQ = ggml_soft_max_inplace(ctx0, KQ);
             }
 
             struct ggml_tensor * KQV = ggml_mul_mat(ctx0, V, KQ);
@@ -3123,9 +3120,8 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
                         for (int dx = 0; dx < 2; dx++) {
                             auto remap = idx[ptr / mpow];
                             remap = remap * mpow + (ptr % mpow);
-                            // auto remap = ptr;
 
-                            positions_data[remap]                 = y + dy;
+                            positions_data[remap]                   = y + dy;
                             positions_data[num_patches + remap]     = x + dx;
                             positions_data[num_patches * 2 + remap] = y + dy;
                             positions_data[num_patches * 3 + remap] = x + dx;
@@ -3220,7 +3216,6 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
             }
         }
 
-
         if (window_idx) ggml_backend_tensor_set(window_idx, idx.data(), 0, ggml_nbytes(window_idx));
         if (inv_window_idx) ggml_backend_tensor_set(inv_window_idx, inv_idx.data(), 0, ggml_nbytes(inv_window_idx));
         if (window_mask) ggml_backend_tensor_set(window_mask, mask.data(), 0, ggml_nbytes(window_mask));

examples/llava/qwen2vl-cli.cpp

@@ -567,76 +567,6 @@ static void debug_dump_img_embed(struct llava_context * ctx_llava, model_output_
     }
 }
 
-
-static void dump_win_attn_mask() {
-    const int image_size_width = 196;
-    const int image_size_height = 140;
-    const int patch_size = 14;
-    const int attn_window_size = 112;
-
-    const int merge_ratio = 2;
-    const int ipw = image_size_width / patch_size;
-    const int iph = image_size_height / patch_size;
-    const int pw = image_size_width / patch_size / merge_ratio;
-    const int ph = image_size_height / patch_size / merge_ratio;
-    const int grid_window = attn_window_size / patch_size / merge_ratio;
-    /*
-    pw * ph = number of tokens output by ViT after apply patch merger
-    ipw * ipw = number of vision token been processed inside ViT
-    */
-
-    std::vector<int> idx(ph * pw);
-    std::vector<int> inv_idx(ph * pw);
-    int dst = 0;
-    // [num_vision_tokens, num_vision_tokens] attention mask tensor
-    int ne = pow(ipw * iph, 2);
-    std::vector<float> mask(ne, std::numeric_limits<float>::lowest());
-    int mask_row = 0;
-
-    for (int y = 0; y < ph; y+=grid_window)
-    {
-        for (int x = 0; x < pw; x+=grid_window)
-        {
-            const int win_h = std::min(grid_window, ph - y);
-            const int win_w = std::min(grid_window, pw - x);
-            const int dst_0 = dst;
-            // group all tokens belong to the same window togather (to a continue range)
-            for (int dy = 0; dy < win_h; dy++) {
-                for (int dx = 0; dx < win_w; dx++) {
-                    const int src = (y + dy) * pw + (x + dx);
-                    assert(src < (int)idx.size());
-                    assert(dst < (int)inv_idx.size());
-                    idx[src] = dst;
-                    inv_idx[dst] = src;
-                    dst++;
-                }
-            }
-
-            for (int r=0; r < win_h * win_w * merge_ratio * merge_ratio; r++) {
-                int row_offset = mask_row * (ipw * iph);
-                std::fill(
-                    mask.begin() + row_offset + (dst_0 * merge_ratio * merge_ratio),
-                    mask.begin() + row_offset + (dst   * merge_ratio * merge_ratio),
-                    0.0);
-                mask_row++;
-            }
-        }
-    }
-
-    auto output_path = "win_attn_mask_fp32.bin";
-
-    std::ofstream outFile(output_path, std::ios::binary);
-    if (outFile.is_open()) {
-        outFile.write(reinterpret_cast<const char*>(mask.data()), ne * sizeof(float));
-
-        outFile.close();
-        std::cout << "Data successfully written to " << output_path << std::endl;
-    } else {
-        std::cerr << "Error opening file!" << std::endl;
-    }
-}
-
-
 #endif