Merge branch 'dygraph' into fix_doc

tools/infer/predict_cls.py

@@ -98,10 +98,10 @@ class TextClassifier(object):
             norm_img_batch = np.concatenate(norm_img_batch)
             norm_img_batch = norm_img_batch.copy()
             starttime = time.time()
-
             self.input_tensor.copy_from_cpu(norm_img_batch)
             self.predictor.run()
             prob_out = self.output_tensors[0].copy_to_cpu()
+            self.predictor.try_shrink_memory()
             cls_result = self.postprocess_op(prob_out)
             elapse += time.time() - starttime
             for rno in range(len(cls_result)):

tools/infer/predict_det.py

@@ -180,7 +180,7 @@ class TextDetector(object):
             preds['maps'] = outputs[0]
         else:
             raise NotImplementedError
-
+        self.predictor.try_shrink_memory()
         post_result = self.postprocess_op(preds, shape_list)
         dt_boxes = post_result[0]['points']
         if self.det_algorithm == "SAST" and self.det_sast_polygon:

tools/infer/predict_rec.py

@@ -237,7 +237,7 @@ class TextRecognizer(object):
                     output = output_tensor.copy_to_cpu()
                     outputs.append(output)
                 preds = outputs[0]
-
+            self.predictor.try_shrink_memory()
             rec_result = self.postprocess_op(preds)
             for rno in range(len(rec_result)):
                 rec_res[indices[beg_img_no + rno]] = rec_result[rno]

tools/infer/utility.py

@@ -128,7 +128,8 @@ def create_predictor(args, mode, logger):
             #config.set_mkldnn_op({'conv2d', 'depthwise_conv2d', 'pool2d', 'batch_norm'})
             args.rec_batch_num = 1
 
-    # config.enable_memory_optim()
+    # enable memory optim
+    config.enable_memory_optim()
     config.disable_glog_info()
 
     config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass")