Accelerate titles' embeddings. (#4492)

### What problem does this PR solve?


### Type of change

- [x] Performance Improvement

deepdoc/vision/layout_recognizer.py

                     "x0": b["bbox"][0] / scale_factor, "x1": b["bbox"][2] / scale_factor,
                     "top": b["bbox"][1] / scale_factor, "bottom": b["bbox"][-1] / scale_factor,
                     "page_number": pn,
-                    } for b in lts if float(b["score"]) >= 0.8 or b["type"] not in self.garbage_layouts]
+                    } for b in lts if float(b["score"]) >= 0.4 or b["type"] not in self.garbage_layouts]
             lts = self.sort_Y_firstly(lts, np.mean(
                 [lt["bottom"] - lt["top"] for lt in lts]) / 2)
             lts = self.layouts_cleanup(bxs, lts)

rag/svr/task_executor.py

 
     tk_count = 0
     if len(tts) == len(cnts):
-        tts_ = np.array([])
-        for i in range(0, len(tts), batch_size):
-            vts, c = mdl.encode(tts[i: i + batch_size])
-            if len(tts_) == 0:
-                tts_ = vts
-            else:
-                tts_ = np.concatenate((tts_, vts), axis=0)
-            tk_count += c
-            callback(prog=0.6 + 0.1 * (i + 1) / len(tts), msg="")
-        tts = tts_
+        vts, c = mdl.encode(tts[0: 1])
+        tts = np.concatenate([vts for _ in range(len(tts))], axis=0)
+        tk_count += c
 
     cnts_ = np.array([])
     for i in range(0, len(cnts), batch_size):