fix: correct dpm++2s_a second model call (#1435 )

refactor: remove is_xl guard wrapper in get_sd_version (#1430 )
fix: skip empty prompt segments around attention range (#1429 )
2026-10-14 05:10:44 +08:00 · 2026-04-18 14:54:41 +08:00 · 2026-04-17 01:53:58 +08:00 · 2026-04-17 01:42:14 +08:00
3 changed files with 63 additions and 60 deletions
@@ -1673,14 +1673,18 @@ struct LLMEmbedder : public Conditioner {
                                                                                  size_t max_length = 100000000) {
        std::vector<std::pair<std::string, float>> parsed_attention;
        if (attn_range.first >= 0 && attn_range.second > 0) {
-            parsed_attention.emplace_back(text.substr(0, attn_range.first), 1.f);
+            if (attn_range.first > 0) {
+                parsed_attention.emplace_back(text.substr(0, attn_range.first), 1.f);
+            }
            if (attn_range.second - attn_range.first > 0) {
                auto new_parsed_attention = parse_prompt_attention(text.substr(attn_range.first, attn_range.second - attn_range.first));
                parsed_attention.insert(parsed_attention.end(),
                                        new_parsed_attention.begin(),
                                        new_parsed_attention.end());
            }
-            parsed_attention.emplace_back(text.substr(attn_range.second), 1.f);
+            if (attn_range.second < text.size()) {
+                parsed_attention.emplace_back(text.substr(attn_range.second), 1.f);
+            }
        } else {
            parsed_attention.emplace_back(text, 1.f);
        }
@@ -953,8 +953,9 @@ static sd::Tensor<float> sample_dpmpp_2s_ancestral(denoise_cb_t model,
            float t_next         = t_fn(sigma_down);
            float h              = t_next - t;
            float s              = t + 0.5f * h;
-            sd::Tensor<float> x2 = (sigma_fn(s) / sigma_fn(t)) * x - (exp(-h * 0.5f) - 1) * denoised;
-            auto denoised2_opt   = model(x2, sigmas[i + 1], i + 1);
+            float sigma_s        = sigma_fn(s);
+            sd::Tensor<float> x2 = (sigma_s / sigma_fn(t)) * x - (exp(-h * 0.5f) - 1) * denoised;
+            auto denoised2_opt   = model(x2, sigma_s, i + 1);
            if (denoised2_opt.empty()) {
                return {};
            }
@@ -1022,65 +1022,63 @@ SDVersion ModelLoader::get_sd_version() {
    bool has_attn_1024               = false;

    for (auto& [name, tensor_storage] : tensor_storage_map) {
-        if (!(is_xl)) {
-            if (tensor_storage.name.find("model.diffusion_model.double_blocks.") != std::string::npos) {
-                is_flux = true;
+        if (tensor_storage.name.find("model.diffusion_model.double_blocks.") != std::string::npos) {
+            is_flux = true;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.nerf_final_layer_conv.") != std::string::npos) {
+            return VERSION_CHROMA_RADIANCE;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.joint_blocks.") != std::string::npos) {
+            return VERSION_SD3;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.transformer_blocks.0.img_mod.1.weight") != std::string::npos) {
+            return VERSION_QWEN_IMAGE;
+        }
+        if (tensor_storage.name.find("llm_adapter.blocks.0.cross_attn.q_proj.weight") != std::string::npos) {
+            return VERSION_ANIMA;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.double_stream_modulation_img.lin.weight") != std::string::npos) {
+            is_flux2 = true;
+        }
+        if (tensor_storage.name.find("single_blocks.47.linear1.weight") != std::string::npos) {
+            has_single_block_47 = true;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.double_blocks.0.img_mlp.gate_proj.weight") != std::string::npos) {
+            return VERSION_OVIS_IMAGE;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.cap_embedder.0.weight") != std::string::npos) {
+            return VERSION_Z_IMAGE;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.layers.0.adaLN_sa_ln.weight") != std::string::npos) {
+            return VERSION_ERNIE_IMAGE;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.blocks.0.cross_attn.norm_k.weight") != std::string::npos) {
+            is_wan = true;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.patch_embedding.weight") != std::string::npos) {
+            patch_embedding_channels = tensor_storage.ne[3];
+        }
+        if (tensor_storage.name.find("model.diffusion_model.img_emb") != std::string::npos) {
+            has_img_emb = true;
+        }
+        if (tensor_storage.name.find("model.diffusion_model.input_blocks.") != std::string::npos ||
+            tensor_storage.name.find("unet.down_blocks.") != std::string::npos) {
+            is_unet = true;
+            if (has_multiple_encoders) {
+                is_xl = true;
            }
-            if (tensor_storage.name.find("model.diffusion_model.nerf_final_layer_conv.") != std::string::npos) {
-                return VERSION_CHROMA_RADIANCE;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.joint_blocks.") != std::string::npos) {
-                return VERSION_SD3;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.transformer_blocks.0.img_mod.1.weight") != std::string::npos) {
-                return VERSION_QWEN_IMAGE;
-            }
-            if (tensor_storage.name.find("llm_adapter.blocks.0.cross_attn.q_proj.weight") != std::string::npos) {
-                return VERSION_ANIMA;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.double_stream_modulation_img.lin.weight") != std::string::npos) {
-                is_flux2 = true;
-            }
-            if (tensor_storage.name.find("single_blocks.47.linear1.weight") != std::string::npos) {
-                has_single_block_47 = true;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.double_blocks.0.img_mlp.gate_proj.weight") != std::string::npos) {
-                return VERSION_OVIS_IMAGE;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.cap_embedder.0.weight") != std::string::npos) {
-                return VERSION_Z_IMAGE;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.layers.0.adaLN_sa_ln.weight") != std::string::npos) {
-                return VERSION_ERNIE_IMAGE;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.blocks.0.cross_attn.norm_k.weight") != std::string::npos) {
-                is_wan = true;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.patch_embedding.weight") != std::string::npos) {
-                patch_embedding_channels = tensor_storage.ne[3];
-            }
-            if (tensor_storage.name.find("model.diffusion_model.img_emb") != std::string::npos) {
-                has_img_emb = true;
-            }
-            if (tensor_storage.name.find("model.diffusion_model.input_blocks.") != std::string::npos ||
-                tensor_storage.name.find("unet.down_blocks.") != std::string::npos) {
-                is_unet = true;
-                if (has_multiple_encoders) {
-                    is_xl = true;
-                }
-            }
-            if (tensor_storage.name.find("conditioner.embedders.1") != std::string::npos ||
-                tensor_storage.name.find("cond_stage_model.1") != std::string::npos ||
-                tensor_storage.name.find("te.1") != std::string::npos) {
-                has_multiple_encoders = true;
-                if (is_unet) {
-                    is_xl = true;
-                }
-            }
-            if (tensor_storage.name.find("model.diffusion_model.input_blocks.8.0.time_mixer.mix_factor") != std::string::npos) {
-                return VERSION_SVD;
+        }
+        if (tensor_storage.name.find("conditioner.embedders.1") != std::string::npos ||
+            tensor_storage.name.find("cond_stage_model.1") != std::string::npos ||
+            tensor_storage.name.find("te.1") != std::string::npos) {
+            has_multiple_encoders = true;
+            if (is_unet) {
+                is_xl = true;
            }
        }
+        if (tensor_storage.name.find("model.diffusion_model.input_blocks.8.0.time_mixer.mix_factor") != std::string::npos) {
+            return VERSION_SVD;
+        }
        if (tensor_storage.name.find("model.diffusion_model.middle_block.1.") != std::string::npos ||
            tensor_storage.name.find("unet.mid_block.resnets.1.") != std::string::npos) {
            has_middle_block_1 = true;
Author	SHA1	Message	Date
Wagner Bruna	2bcff67480	fix: correct dpm++2s_a second model call (#1435 )	2026-04-18 14:54:41 +08:00
leejet	a564fdf642	refactor: remove is_xl guard wrapper in get_sd_version (#1430 )	2026-04-17 01:53:58 +08:00
leejet	84fc5446d2	fix: skip empty prompt segments around attention range (#1429 )	2026-04-17 01:42:14 +08:00