diff --git a/framework/e2e/PaddleLT_new/binary_search.py b/framework/e2e/PaddleLT_new/binary_search.py
index 78bf7b6af0..f3a2902def 100644
--- a/framework/e2e/PaddleLT_new/binary_search.py
+++ b/framework/e2e/PaddleLT_new/binary_search.py
@@ -62,6 +62,8 @@ def __init__(self, commit_list, title, layerfile, testing, perf_decay=None, test
         self.test_obj = test_obj
         self.py_cmd = os.environ.get("python_ver")
         self.testing_mode = os.environ.get("TESTING_MODE")
+        self.device_place_id = 0
+        self.timeout = 300
 
     def _status_print(self, exit_code, status_str):
         """
@@ -82,8 +84,8 @@ def _install_paddle(self, commit_id):
 
         whl_link = (
             "https://paddle-qa.bj.bcebos.com/paddle-pipe"
-            "line/Develop-GpuAll-LinuxCentos-Gcc82-Cuda112-Trtoff-Py38-Compile/{}/paddle"
-            "paddle_gpu-0.0.0-cp38-cp38-linux_x86_64.whl".format(commit_id)
+            "line/Develop-GpuSome-LinuxCentos-Gcc82-Cuda118-Cudnn86-Trt85-Py310-CINN-Compile/{}/paddle"
+            "paddle_gpu-0.0.0-cp310-cp310-linux_x86_64.whl".format(commit_id)
         )
         exit_code = os.system(f"{self.py_cmd} -m pip install {whl_link}")
         self._status_print(exit_code=exit_code, status_str="install paddlepaddle-gpu")
@@ -105,7 +107,8 @@ def _precision_debug(self, commit_id):
         exit_code = os.system(
             f"cp -r PaddleLT.py {self.title}.py && "
             f"{self.py_cmd} -m pytest {self.title}.py --title={self.title} "
-            f"--layerfile={self.layerfile} --testing={self.testing}"
+            f"--layerfile={self.layerfile} --testing={self.testing} "
+            f"--device_place_id={self.device_place_id} --timeout={self.timeout}"
         )
 
         if exit_code > 0:
@@ -168,8 +171,8 @@ def _commit_locate(self, commits):
     if not os.path.exists("paddle"):
         os.system("git clone -b develop http://github.com/paddlepaddle/paddle.git")
     os.chdir(os.path.join(cur_path, "paddle"))
-    start_commit = "f651ac5cf387c56488b52fcc6456a63e9eb73086"  # 成功commit
-    end_commit = "9d5f31687cce16a976256723a70df4550085d685"  # 失败commit
+    start_commit = "4ac66e4319740d65eb3b2a9e80b4a9f989083099"  # 成功commit
+    end_commit = "81dc24b20d9a016dd4e92e76d2849cc9e3d0f8c8"  # 失败commit
     commits = get_commits(start=start_commit, end=end_commit)
     save_pickle(data=commits, filename="candidate_commits.pickle")
     print("the candidate commits is {}".format(commits))
@@ -178,8 +181,8 @@ def _commit_locate(self, commits):
     final_commit = BinarySearch(
         commit_list=commits,
         title="PrecisionBS",
-        layerfile="./layercase/sublayer1000/Clas_cases/CSWinTransformer_CSWinTransformer_base_384/SIR_5.py",
-        testing="yaml/dy^dy2stcinn_eval.yml",
+        layerfile="./layercase/sublayer1000/Det_cases/ppyolo_ppyolo_r50vd_dcn_1x_coco/SIR_58.py",
+        testing="yaml/dy^dy2stcinn_train_inputspec.yml",
         perf_decay=None,  # ["dy2st_eval_cinn_perf", 0.042814, -0.3]
         test_obj=LayerTest,
     )._commit_locate(commits)
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_eval.py b/framework/e2e/PaddleLT_new/engine/paddle_eval.py
index 19df5debf4..0c9f3e564a 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_eval.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_eval.py
@@ -24,7 +24,7 @@ class LayerEval(object):
     """
 
     # def __init__(self, testing, layerfile, device_id):
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -36,6 +36,8 @@ def __init__(self, testing, layerfile, device_place_id):
         # paddle.set_device("{}:{}".format(str(self.device), str(device_id)))
 
         self.testing = testing
+        self.upstream_net = upstream_net
+        self.return_net_instance = self.testing.get("return_net_instance", "False")
         self.model_dtype = self.testing.get("model_dtype")
         paddle.set_default_dtype(self.model_dtype)
 
@@ -53,7 +55,10 @@ def _net_input(self):
     def _net_instant(self):
         """get net"""
         reset(self.seed)
-        net = BuildLayer(layerfile=self.layerfile).get_layer()
+        if self.upstream_net:
+            net = self.upstream_net
+        else:
+            net = BuildLayer(layerfile=self.layerfile).get_layer()
         return net
 
     def _net_input_and_spec(self):
@@ -85,7 +90,10 @@ def dy_eval(self):
         net = self._net_instant()
         net.eval()
         logit = net(*self._net_input())
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval(self):
         """dy2st eval"""
@@ -94,7 +102,10 @@ def dy2st_eval(self):
         st_net = paddle.jit.to_static(net, full_graph=True)
         st_net.eval()
         logit = st_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": st_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval_inputspec(self):
         """dy2st eval"""
@@ -104,7 +115,10 @@ def dy2st_eval_inputspec(self):
         st_net = paddle.jit.to_static(net, full_graph=True, input_spec=input_spec)
         st_net.eval()
         logit = st_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": st_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval_static_inputspec(self):
         """dy2st eval"""
@@ -114,7 +128,10 @@ def dy2st_eval_static_inputspec(self):
         st_net = paddle.jit.to_static(net, full_graph=True, input_spec=input_spec)
         st_net.eval()
         logit = st_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": st_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval_cinn(self):
         """dy2st cinn eval"""
@@ -126,7 +143,10 @@ def dy2st_eval_cinn(self):
         cinn_net = paddle.jit.to_static(net, build_strategy=build_strategy, full_graph=True)
         cinn_net.eval()
         logit = cinn_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval_cinn_inputspec(self):
         """dy2st cinn eval with inputspec"""
@@ -139,7 +159,10 @@ def dy2st_eval_cinn_inputspec(self):
         cinn_net = paddle.jit.to_static(net, build_strategy=build_strategy, full_graph=True, input_spec=input_spec)
         cinn_net.eval()
         logit = cinn_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     def dy2st_eval_cinn_static_inputspec(self):
         """dy2st cinn eval with inputspec"""
@@ -152,7 +175,10 @@ def dy2st_eval_cinn_static_inputspec(self):
         cinn_net = paddle.jit.to_static(net, build_strategy=build_strategy, full_graph=True, input_spec=input_spec)
         cinn_net.eval()
         logit = cinn_net(*data)
-        return {"logit": logit}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit}, "net": None}
 
     # def dy2st_eval_cinn_inputspec_legacy_2(self):
     #     """dy2st cinn eval with inputspec"""
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_eval_bm.py b/framework/e2e/PaddleLT_new/engine/paddle_eval_bm.py
index 3426333302..5bf70b6fe4 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_eval_bm.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_eval_bm.py
@@ -24,7 +24,7 @@ class LayerEvalBM(object):
     """
 
     # def __init__(self, testing, layerfile, device_id):
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -43,6 +43,8 @@ def __init__(self, testing, layerfile, device_place_id):
         self.statis_round = 6
 
         self.testing = testing
+        self.upstream_net = upstream_net
+        # self.return_net_instance = self.testing.get("return_net_instance", "False")
         self.model_dtype = self.testing.get("model_dtype")
         paddle.set_default_dtype(self.model_dtype)
 
@@ -53,7 +55,10 @@ def __init__(self, testing, layerfile, device_place_id):
     def _net_instant(self):
         """get net and data"""
         reset(self.seed)
-        net = BuildLayer(layerfile=self.layerfile).get_layer()
+        if self.upstream_net:
+            net = self.upstream_net
+        else:
+            net = BuildLayer(layerfile=self.layerfile).get_layer()
         return net
 
     def _set_cinn_flags(self):
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_export.py b/framework/e2e/PaddleLT_new/engine/paddle_export.py
index 8a54af176d..87ba4c566b 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_export.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_export.py
@@ -20,7 +20,7 @@ class LayerExport(object):
     构建Layer导出的通用类
     """
 
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -30,6 +30,8 @@ def __init__(self, testing, layerfile, device_place_id):
         paddle.set_device(f"{self.device}:{device_place_id}")
 
         self.testing = testing
+        self.upstream_net = upstream_net
+        # self.return_net_instance = self.testing.get("return_net_instance", "False")
         self.model_dtype = self.testing.get("model_dtype")
         paddle.set_default_dtype(self.model_dtype)
 
@@ -48,7 +50,10 @@ def _net_input(self):
     def _net_instant(self):
         """get net"""
         reset(self.seed)
-        net = BuildLayer(layerfile=self.layerfile).get_layer()
+        if self.upstream_net:
+            net = self.upstream_net
+        else:
+            net = BuildLayer(layerfile=self.layerfile).get_layer()
         return net
 
     def _net_input_and_spec(self):
@@ -77,6 +82,7 @@ def jit_save(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(st_net, path=os.path.join(self.path, self.layername, "jit_save"))
+        return {"res": None}
 
     def jit_save_inputspec(self):
         """jit.save(layer)"""
@@ -90,6 +96,7 @@ def jit_save_inputspec(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(st_net, path=os.path.join(self.path, self.layername, "jit_save_inputspec"))
+        return {"res": None}
 
     def jit_save_static_inputspec(self):
         """jit.save(layer)"""
@@ -103,6 +110,7 @@ def jit_save_static_inputspec(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(st_net, path=os.path.join(self.path, self.layername, "jit_save_static_inputspec"))
+        return {"res": None}
 
     def jit_save_cinn(self):
         """jit.save(layer)"""
@@ -117,6 +125,7 @@ def jit_save_cinn(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(cinn_net, path=os.path.join(self.path, self.layername, "jit_save_cinn"))
+        return {"res": None}
 
     def jit_save_cinn_inputspec(self):
         """jit.save(layer)"""
@@ -132,6 +141,7 @@ def jit_save_cinn_inputspec(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(cinn_net, path=os.path.join(self.path, self.layername, "jit_save_cinn_inputspec"))
+        return {"res": None}
 
     def jit_save_cinn_static_inputspec(self):
         """jit.save(layer)"""
@@ -147,3 +157,4 @@ def jit_save_cinn_static_inputspec(self):
 
         # paddle.jit.save(net, path=os.path.join(self.path, self.case))
         paddle.jit.save(cinn_net, path=os.path.join(self.path, self.layername, "jit_save_cinn_static_inputspec"))
+        return {"res": None}
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_infer.py b/framework/e2e/PaddleLT_new/engine/paddle_infer.py
index 8ac3b5be7e..4ab35e7f1a 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_infer.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_infer.py
@@ -14,13 +14,15 @@
 from generator.builder_layer import BuildLayer
 from generator.builder_data import BuildData
 
+from tools.logger import Logger
+
 
 class LayerInfer(object):
     """
     构建Layer预测的通用类
     """
 
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -41,7 +43,8 @@ def paddle_infer_gpu(self):
         """infer load (layer)"""
         reset(self.seed)
         if not os.path.exists(self.path + ".pdiparams"):
-            return "pass"
+            Logger("paddle_infer_gpu").get_log().info("该子图export未产出pdiparams, 所以跳过infer测试")
+            return {"res": {"logit": None}}
 
         config = paddle_infer.Config(self.path + ".pdmodel", self.path + ".pdiparams")
         config.enable_use_gpu(1000, int(self.device_id))
@@ -63,13 +66,14 @@ def paddle_infer_gpu(self):
         else:
             output_handle = predictor.get_output_handle(output_names[0])
             infer_res = output_handle.copy_to_cpu()
-        return {"logit": infer_res}
+        return {"res": {"logit": infer_res}}
 
     def paddle_infer_cpu(self):
         """infer load (layer)"""
         reset(self.seed)
         if not os.path.exists(self.path + ".pdiparams"):
-            return "pass"
+            Logger("paddle_infer_cpu").get_log().info("该子图export未产出pdiparams, 所以跳过infer测试")
+            return {"res": {"logit": None}}
 
         config = paddle_infer.Config(self.path + ".pdmodel", self.path + ".pdiparams")
 
@@ -92,13 +96,14 @@ def paddle_infer_cpu(self):
         else:
             output_handle = predictor.get_output_handle(output_names[0])
             infer_res = output_handle.copy_to_cpu()
-        return {"logit": infer_res}
+        return {"res": {"logit": infer_res}}
 
     def paddle_infer_mkldnn(self):
         """infer load (layer)"""
         reset(self.seed)
         if not os.path.exists(self.path + ".pdiparams"):
-            return "pass"
+            Logger("paddle_infer_mkldnn").get_log().info("该子图export未产出pdiparams, 所以跳过infer测试")
+            return {"res": {"logit": None}}
 
         config = paddle_infer.Config(self.path + ".pdmodel", self.path + ".pdiparams")
 
@@ -123,13 +128,14 @@ def paddle_infer_mkldnn(self):
         else:
             output_handle = predictor.get_output_handle(output_names[0])
             infer_res = output_handle.copy_to_cpu()
-        return {"logit": infer_res}
+        return {"res": {"logit": infer_res}}
 
     def paddle_infer_ort(self):
         """infer load (layer)"""
         reset(self.seed)
         if not os.path.exists(self.path + ".pdiparams"):
-            return "pass"
+            Logger("paddle_infer_ort").get_log().info("该子图export未产出pdiparams, 所以跳过infer测试")
+            return {"res": {"logit": None}}
 
         config = paddle_infer.Config(self.path + ".pdmodel", self.path + ".pdiparams")
 
@@ -153,13 +159,14 @@ def paddle_infer_ort(self):
         else:
             output_handle = predictor.get_output_handle(output_names[0])
             infer_res = output_handle.copy_to_cpu()
-        return {"logit": infer_res}
+        return {"res": {"logit": infer_res}}
 
     def paddle_infer_new_exc_pir(self):
         """infer load (layer)"""
         reset(self.seed)
         if not os.path.exists(self.path + ".pdiparams"):
-            return "pass"
+            Logger("paddle_infer_new_exc_pir").get_log().info("该子图export未产出pdiparams, 所以跳过infer测试")
+            return {"res": {"logit": None}}
 
         config = paddle_infer.Config(self.path + ".json", self.path + ".pdiparams")
         # config = paddle_infer.Config(self.path, 'inference')
@@ -186,4 +193,4 @@ def paddle_infer_new_exc_pir(self):
         else:
             output_handle = predictor.get_output_handle(output_names[0])
             infer_res = output_handle.copy_to_cpu()
-        return {"logit": infer_res}
+        return {"res": {"logit": infer_res}}
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_train.py b/framework/e2e/PaddleLT_new/engine/paddle_train.py
index 3480f6f686..52aec07e71 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_train.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_train.py
@@ -24,7 +24,7 @@ class LayerTrain(object):
     """
 
     # def __init__(self, testing, layerfile, device_id):
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -36,6 +36,8 @@ def __init__(self, testing, layerfile, device_place_id):
         # paddle.set_device("{}:{}".format(str(self.device), str(device_id)))
 
         self.testing = testing
+        self.upstream_net = upstream_net
+        self.return_net_instance = self.testing.get("return_net_instance", "False")
         self.model_dtype = self.testing.get("model_dtype")
         paddle.set_default_dtype(self.model_dtype)
 
@@ -51,7 +53,10 @@ def _net_input(self):
     def _net_instant(self):
         """get net"""
         reset(self.seed)
-        net = BuildLayer(layerfile=self.layerfile).get_layer()
+        if self.upstream_net:
+            net = self.upstream_net
+        else:
+            net = BuildLayer(layerfile=self.layerfile).get_layer()
         return net
 
     def _net_optimizer(self):
@@ -135,8 +140,12 @@ def dy_train(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy_train").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy_dp_train(self):
         """dygraph data parallel train"""
@@ -166,8 +175,13 @@ def dy_dp_train(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy_dp_train").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     # def dy_train_dl(self):
     #     """dygraph train with dataloader"""
@@ -217,8 +231,13 @@ def dy2st_train(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": st_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy2st_train_inputspec(self):
         """dy2st cinn train with inputspec"""
@@ -244,8 +263,13 @@ def dy2st_train_inputspec(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train_inputspec").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": st_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy2st_train_static_inputspec(self):
         """dy2st cinn train with inputspec"""
@@ -271,8 +295,13 @@ def dy2st_train_static_inputspec(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train_static_inputspec").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": st_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy2st_train_cinn(self):
         """dy2st cinn train"""
@@ -284,23 +313,28 @@ def dy2st_train_cinn(self):
         net.train()
         build_strategy = paddle.static.BuildStrategy()
         build_strategy.build_cinn_pass = True
-        st_net = paddle.jit.to_static(net, build_strategy=build_strategy, full_graph=True)
+        cinn_net = paddle.jit.to_static(net, build_strategy=build_strategy, full_graph=True)
 
         # 构建optimizer用于训练
-        if st_net.parameters():
-            opt = optimizer.get_opt(net=st_net)
+        if cinn_net.parameters():
+            opt = optimizer.get_opt(net=cinn_net)
 
         for epoch in range(self.step):
-            logit = st_net(*data)
+            logit = cinn_net(*data)
             # 构建loss用于训练
             dy_loss = loss.get_loss(logit)
             dy_loss.backward()
-            if st_net.parameters():
+            if cinn_net.parameters():
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train_cinn").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy2st_train_cinn_inputspec(self):
         """dy2st cinn train with inputspec"""
@@ -328,8 +362,13 @@ def dy2st_train_cinn_inputspec(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train_cinn_inputspec").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
 
     def dy2st_train_cinn_static_inputspec(self):
         """dy2st cinn train with inputspec"""
@@ -357,5 +396,10 @@ def dy2st_train_cinn_static_inputspec(self):
                 opt.step()
                 opt.clear_grad()
 
+        Logger("dy2st_train_cinn_static_inputspec").get_log().info(f"已完成 {epoch} 轮训练")
         data_grad = self._get_data_grad(data)
-        return {"logit": logit, "data_grad": data_grad}
+        # return {"logit": logit, "data_grad": data_grad}
+        if self.return_net_instance == "True":
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": cinn_net}
+        else:
+            return {"res": {"logit": logit, "data_grad": data_grad}, "net": None}
diff --git a/framework/e2e/PaddleLT_new/engine/paddle_train_bm.py b/framework/e2e/PaddleLT_new/engine/paddle_train_bm.py
index 82384f554a..c17564a189 100644
--- a/framework/e2e/PaddleLT_new/engine/paddle_train_bm.py
+++ b/framework/e2e/PaddleLT_new/engine/paddle_train_bm.py
@@ -26,7 +26,7 @@ class LayerTrainBM(object):
     """
 
     # def __init__(self, testing, layerfile, device_id):
-    def __init__(self, testing, layerfile, device_place_id):
+    def __init__(self, testing, layerfile, device_place_id, upstream_net):
         """
         初始化
         """
@@ -45,6 +45,8 @@ def __init__(self, testing, layerfile, device_place_id):
         self.statis_round = 6
 
         self.testing = testing
+        self.upstream_net = upstream_net
+        # self.return_net_instance = self.testing.get("return_net_instance", "False")
         self.model_dtype = self.testing.get("model_dtype")
         paddle.set_default_dtype(self.model_dtype)
 
@@ -56,7 +58,10 @@ def __init__(self, testing, layerfile, device_place_id):
     def _net_instant(self):
         """get net and data"""
         reset(self.seed)
-        net = BuildLayer(layerfile=self.layerfile).get_layer()
+        if self.upstream_net:
+            net = self.upstream_net
+        else:
+            net = BuildLayer(layerfile=self.layerfile).get_layer()
         return net
 
     def _net_optimizer(self):
diff --git a/framework/e2e/PaddleLT_new/layerApicase/nn_sublayer/dropout2d_0_func.py b/framework/e2e/PaddleLT_new/layerApicase/nn_sublayer/dropout2d_0_func.py
index 80c307ce7e..bea163ff87 100644
--- a/framework/e2e/PaddleLT_new/layerApicase/nn_sublayer/dropout2d_0_func.py
+++ b/framework/e2e/PaddleLT_new/layerApicase/nn_sublayer/dropout2d_0_func.py
@@ -15,7 +15,7 @@ def forward(self, x, ):
         """
         forward
         """
-        out = paddle.nn.functional.dropout2d(x,  p=paddle.to_tensor([0.5], dtype='float32', stop_gradient=False), training=True, )
+        out = paddle.nn.functional.dropout2d(x,  p=paddle.to_tensor([0.5], dtype='float32', stop_gradient=False), training=self.training, )
         return out
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/perf245/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py b/framework/e2e/PaddleLT_new/layercase/perf245/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
index 0050a41c7a..8458707449 100644
--- a/framework/e2e/PaddleLT_new/layercase/perf245/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
+++ b/framework/e2e/PaddleLT_new/layercase/perf245/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
@@ -19,7 +19,7 @@ def forward(
     ):
         var_3 = paddle.nn.functional.common.interpolate(var_0, scale_factor=2, mode='bilinear', align_corners=True)
         var_4 = paddle.tensor.manipulation.concat([var_1, var_3], axis=1)
-        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=True, data_format='NCHW', name=None)
+        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=self.training, data_format='NCHW', name=None)
         var_6 = paddle.nn.functional.conv._conv_nd(var_5, self.parameter_0, bias=None, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_7 = paddle.nn.functional.common.interpolate(var_6, scale_factor=2, mode='bilinear', align_corners=True)
         var_8 = paddle.nn.functional.common.interpolate(var_2, scale_factor=2, mode='bilinear', align_corners=True)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
index 53555f906a..1303d53647 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_5.matmul(var_8)
         var_10 = var_9.__mul__(0.125)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_7)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((-1, 198, 192,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_2, bias=self.parameter_4, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_56.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_56.py
index 1ca00a2704..8dcba83093 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_56.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_56.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_5.matmul(var_8)
         var_10 = var_9.__mul__(0.125)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_7)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((-1, 198, 192,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_1, bias=self.parameter_2, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_4.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_4.py
index a54e05ddde..4e42dae425 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_4.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_4.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_5.matmul(var_8)
         var_10 = var_9.__mul__(0.125)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_7)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((-1, 197, 192,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_3, bias=self.parameter_5, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_56.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_56.py
index a15e7b6858..fae2239e3d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_56.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/DeiT_DeiT_tiny_patch16_224/SIR_56.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_5.matmul(var_8)
         var_10 = var_9.__mul__(0.125)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_7)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((-1, 197, 192,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_0, bias=self.parameter_5, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_140.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_140.py
index d359417040..a6464096e4 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_140.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_140.py
@@ -21,7 +21,7 @@ def forward(
     ):
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
-        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
index 781956af76..486ab89d99 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
@@ -21,7 +21,7 @@ def forward(
     ):
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
-        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_39.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_39.py
index 6e6a9b8a56..507808cac9 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_39.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_39.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = paddle.tensor.manipulation.squeeze(var_1, axis=[2, 3])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_40.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_40.py
index 7262a08d42..7fa2530d30 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_40.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Inception_InceptionV4/SIR_40.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = paddle.tensor.manipulation.squeeze(var_1, axis=[2, 3])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
index 8c16e59c62..ba72d48d57 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = var_1.reshape([43, 320])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_27.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_27.py
index bb9fb3dc8a..5aafee130c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_27.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/MobileViT_MobileViT_XXS/SIR_27.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = var_1.reshape([11, 320])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_41.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
index 4e0c49bada..c4502c74ad 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.avg_pool2d(var_0, kernel_size=[7, 7])
         var_2 = var_1.flatten(1)
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=True)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=self.training)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_42.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_42.py
index de558608ea..ab4a248bb6 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_42.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/PeleeNet_PeleeNet/SIR_42.py
@@ -22,7 +22,7 @@ def forward(
         paddle.seed(33)
         var_1 = paddle.nn.functional.pooling.avg_pool2d(var_0, kernel_size=[7, 7])
         var_2 = var_1.flatten(1)
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=True)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=self.training)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
index a9851348c7..5ba1a6fd5f 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [22, 3840, 1, 1], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_3 = var_2.squeeze(axis=-1)
         var_4 = var_3.squeeze(axis=-1)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_61.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_61.py
index 42ed5ee84d..5bc6700ecc 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_61.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/ReXNet_ReXNet_3_0/SIR_61.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [10, 3840, 1, 1], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_0, bias=self.parameter_1, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_3 = var_2.squeeze(axis=-1)
         var_4 = var_3.squeeze(axis=-1)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
index 16a7c5d6e9..0d1a93c7b3 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
@@ -281,7 +281,7 @@ def forward(
         var_59 = paddle.nn.functional.conv._conv_nd(var_56, self.parameter_35, bias=self.parameter_48, stride=[1, 1], padding=[1, 1], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_60 = paddle.nn.functional.activation.relu(var_59)
         var_61 = paddle.tensor.manipulation.concat([var_58, var_60], axis=1)
-        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_63 = paddle.nn.functional.conv._conv_nd(var_62, self.parameter_44, bias=self.parameter_1, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_64 = paddle.nn.functional.activation.relu(var_63)
         var_65 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_64, output_size=1, data_format='NCHW', name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_1.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_1.py
index 0ca56bfe59..850fafa090 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_1.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_1.py
@@ -281,7 +281,7 @@ def forward(
         var_59 = paddle.nn.functional.conv._conv_nd(var_56, self.parameter_39, bias=self.parameter_1, stride=[1, 1], padding=[1, 1], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_60 = paddle.nn.functional.activation.relu(var_59)
         var_61 = paddle.tensor.manipulation.concat([var_58, var_60], axis=1)
-        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_63 = paddle.nn.functional.conv._conv_nd(var_62, self.parameter_15, bias=self.parameter_17, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_64 = paddle.nn.functional.activation.relu(var_63)
         var_65 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_64, output_size=1, data_format='NCHW', name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_108.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_108.py
index 1e3eaa1721..c31613494b 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_108.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_108.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[384], weight=self.parameter_2, bias=self.parameter_1, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_136.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_136.py
index 9c4d75e67d..49eb091a1d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_136.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_136.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[768], weight=self.parameter_0, bias=self.parameter_3, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_14.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_14.py
index f45422bef1..3f5fc8286c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_14.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_14.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[192], weight=self.parameter_3, bias=self.parameter_2, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_2.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_2.py
index 4b6dad9154..41f6e276b4 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_2.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_2.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[96], weight=self.parameter_1, bias=self.parameter_0, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_26.py
index c171476c89..0a1dc90722 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_26.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[384], weight=self.parameter_0, bias=self.parameter_2, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_70.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_70.py
index 9a4e976ff5..cc772efff0 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_70.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_70.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[768], weight=self.parameter_3, bias=self.parameter_2, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_84.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_84.py
index 93e93954c5..49a42602e7 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_84.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_84.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[96], weight=self.parameter_2, bias=self.parameter_0, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_96.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_96.py
index 8a66e139e3..58f5087a6e 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_96.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Twins_alt_gvt_base/SIR_96.py
@@ -32,7 +32,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[192], weight=self.parameter_1, bias=self.parameter_0, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_35.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
index 4bfec374f2..b6b66a1044 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [22, 2048, 10, 10], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_2 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_1, output_size=1, data_format='NCHW', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_55.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_55.py
index 994ccab514..8b1d9baf1e 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_55.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Clas_cases/Xception_Xception65_deeplab/SIR_55.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [10, 2048, 10, 10], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_2 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_1, output_size=1, data_format='NCHW', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
index 0ea90a31ef..c41101de69 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
@@ -36,7 +36,7 @@ def forward(
         var_6 = var_5.reshape([-1, 96, 200, 304])
         var_7 = var_6.flatten(2)
         var_8 = var_7.transpose([0, 2, 1])
-        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_9
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_2x_coco/SIR_3.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_2x_coco/SIR_3.py
index 7f8aeb5de0..bb79c07a7d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_2x_coco/SIR_3.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_2x_coco/SIR_3.py
@@ -36,7 +36,7 @@ def forward(
         var_6 = var_5.reshape([-1, 96, 136, 160])
         var_7 = var_6.flatten(2)
         var_8 = var_7.transpose([0, 2, 1])
-        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_9
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
index 4f08d13720..2b6d15003f 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
@@ -45,14 +45,14 @@ def forward(
         var_1,    # (shape: [1, 169, 1024], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_2 = paddle.nn.functional.common.dropout(var_0, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_2 = paddle.nn.functional.common.dropout(var_0, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_3 = var_1.__add__(var_2)
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[1024], weight=self.parameter_5, bias=self.parameter_3, epsilon=1e-05)
         var_5 = paddle.nn.functional.common.linear(x=var_4, weight=self.parameter_7, bias=self.parameter_0, name=None)
         var_6 = paddle.nn.functional.activation.gelu(var_5)
-        var_7 = paddle.nn.functional.common.dropout(var_6, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_7 = paddle.nn.functional.common.dropout(var_6, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_8 = paddle.nn.functional.common.linear(x=var_7, weight=self.parameter_6, bias=self.parameter_1, name=None)
-        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_10 = var_4.__add__(var_9)
         var_11 = paddle.nn.functional.norm.layer_norm(var_10, normalized_shape=[1024], weight=self.parameter_2, bias=self.parameter_4, epsilon=1e-05)
         return var_11
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
index 89f59aeadf..3636681783 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
@@ -61,12 +61,12 @@ def forward(
         var_15 = var_11.matmul(var_14)
         var_16 = var_15.__mul__(0.125)
         var_17 = paddle.nn.functional.activation.softmax(var_16, axis=-1)
-        var_18 = paddle.nn.functional.common.dropout(var_17, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_18 = paddle.nn.functional.common.dropout(var_17, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_19 = var_18.matmul(var_13)
         var_20 = var_19.transpose((0, 2, 1, 3,))
         var_21 = var_20.reshape((-1, var_3, var_4,))
         var_22 = paddle.nn.functional.common.linear(x=var_21, weight=self.parameter_4, bias=self.parameter_0, name=None)
-        var_23 = paddle.nn.functional.common.dropout(var_22, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_23 = paddle.nn.functional.common.dropout(var_22, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_24 = self.parameter_2.__mul__(var_23)
         return var_24
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_30.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_30.py
index a1109994e7..8176e0a9a7 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_30.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_30.py
@@ -49,12 +49,12 @@ def forward(
         var_11 = var_7.matmul(var_10)
         var_12 = var_11.__add__(var_1)
         var_13 = paddle.nn.functional.activation.softmax(var_12, axis=-1)
-        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_15 = var_14.matmul(var_9)
         var_16 = var_15.transpose((0, 2, 1, 3,))
         var_17 = var_16.reshape((0, -1, 64,))
         var_18 = paddle.nn.functional.common.linear(x=var_17, weight=self.parameter_3, bias=self.parameter_4, name=None)
-        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_19
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_43.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_43.py
index 191fd0ef15..3b3055ecc9 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_43.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_43.py
@@ -49,12 +49,12 @@ def forward(
         var_11 = var_7.matmul(var_10)
         var_12 = var_11.__add__(var_1)
         var_13 = paddle.nn.functional.activation.softmax(var_12, axis=-1)
-        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_15 = var_14.matmul(var_9)
         var_16 = var_15.transpose((0, 2, 1, 3,))
         var_17 = var_16.reshape((0, -1, 128,))
         var_18 = paddle.nn.functional.common.linear(x=var_17, weight=self.parameter_0, bias=self.parameter_3, name=None)
-        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_19
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_57.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_57.py
index 427e9ed33d..7e158c4020 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_57.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_57.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_7.transpose((0, 1, 3, 2,))
         var_10 = var_6.matmul(var_9)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_8)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((0, -1, 128,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_2, bias=self.parameter_4, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_72.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_72.py
index bc00da2df7..dbaa521272 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_72.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet/SIR_72.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_7.transpose((0, 1, 3, 2,))
         var_10 = var_6.matmul(var_9)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_8)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((0, -1, 256,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_2, bias=self.parameter_5, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_13.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_13.py
index 63b041378a..711d2dfb2f 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_13.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_13.py
@@ -49,12 +49,12 @@ def forward(
         var_11 = var_7.matmul(var_10)
         var_12 = var_11.__add__(var_1)
         var_13 = paddle.nn.functional.activation.softmax(var_12, axis=-1)
-        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_15 = var_14.matmul(var_9)
         var_16 = var_15.transpose((0, 2, 1, 3,))
         var_17 = var_16.reshape((0, -1, 64,))
         var_18 = paddle.nn.functional.common.linear(x=var_17, weight=self.parameter_2, bias=self.parameter_1, name=None)
-        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_19
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_26.py
index 11ba3955c9..8badc02f9d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_26.py
@@ -49,12 +49,12 @@ def forward(
         var_11 = var_7.matmul(var_10)
         var_12 = var_11.__add__(var_1)
         var_13 = paddle.nn.functional.activation.softmax(var_12, axis=-1)
-        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_15 = var_14.matmul(var_9)
         var_16 = var_15.transpose((0, 2, 1, 3,))
         var_17 = var_16.reshape((0, -1, 128,))
         var_18 = paddle.nn.functional.common.linear(x=var_17, weight=self.parameter_4, bias=self.parameter_5, name=None)
-        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_19
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_40.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_40.py
index d6b8dc3a04..0cd4040b7c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_40.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_40.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_7.transpose((0, 1, 3, 2,))
         var_10 = var_6.matmul(var_9)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_8)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((0, -1, 128,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_4, bias=self.parameter_5, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_55.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_55.py
index 09eab4e63e..02eec8561c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_55.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Ocr_cases/rec_rec_svtrnet_ch/SIR_55.py
@@ -47,12 +47,12 @@ def forward(
         var_9 = var_7.transpose((0, 1, 3, 2,))
         var_10 = var_6.matmul(var_9)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_8)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((0, -1, 256,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_1, bias=self.parameter_3, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
index 4bbe67c27e..ca4c96ba7b 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
@@ -39,13 +39,13 @@ def forward(
     ):
         paddle.seed(33)
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_2, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_5, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
index a441be2c45..1f236957a3 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
@@ -39,13 +39,13 @@ def forward(
     ):
         paddle.seed(33)
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_5, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_2, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/dnlnet_dnlnet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/dnlnet_dnlnet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
index a85af7d67c..245b1869d9 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/dnlnet_dnlnet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/dnlnet_dnlnet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 512, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_cityscapes_1024x512_80k/SIR_35.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_cityscapes_1024x512_80k/SIR_35.py
index 630ea7fb36..50141e7228 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_cityscapes_1024x512_80k/SIR_35.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_cityscapes_1024x512_80k/SIR_35.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 256, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_voc12aug_512x512_40k/SIR_35.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_voc12aug_512x512_40k/SIR_35.py
index e76ab9ea62..2b7bc36405 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_voc12aug_512x512_40k/SIR_35.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/emanet_emanet_resnet101_os8_voc12aug_512x512_40k/SIR_35.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 256, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_10.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_10.py
index 9811b6d1a5..d776f3b9bd 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_10.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_10.py
@@ -12,7 +12,7 @@ def forward(
         var_0,    # (shape: [1, 64, 128, 256], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.01, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.01, training=self.training, data_format='NCHW', name=None)
         return var_1
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_20.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_20.py
index 61dcb2448f..cd9750ebe7 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_20.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_20.py
@@ -13,7 +13,7 @@ def forward(
         var_1,    # (shape: [1, 64, 128, 256], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.01, training=True, data_format='NCHW', name=None)
+        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.01, training=self.training, data_format='NCHW', name=None)
         var_3 = var_1.__add__(var_2)
         return var_3
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
index 759ca9ccb4..323d9c6c5b 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
@@ -12,7 +12,7 @@ def forward(
         var_0,    # (shape: [1, 128, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         return var_1
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
index 6dfa5ac413..85ffe6df02 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
@@ -13,7 +13,7 @@ def forward(
         var_1,    # (shape: [1, 128, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_3 = var_1.__add__(var_2)
         return var_3
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
index 17e1a3501f..b350ecda71 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
@@ -20,7 +20,7 @@ def forward(
         paddle.seed(33)
         var_3 = paddle.nn.functional.common.interpolate(var_0, scale_factor=2, mode='bilinear', align_corners=True)
         var_4 = paddle.tensor.manipulation.concat([var_1, var_3], axis=1)
-        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=True, data_format='NCHW', name=None)
+        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=self.training, data_format='NCHW', name=None)
         var_6 = paddle.nn.functional.conv._conv_nd(var_5, self.parameter_0, bias=None, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_7 = paddle.nn.functional.common.interpolate(var_6, scale_factor=2, mode='bilinear', align_corners=True)
         var_8 = paddle.nn.functional.common.interpolate(var_2, scale_factor=2, mode='bilinear', align_corners=True)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet101_os8_voc12aug_512x512_40k/SIR_38.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet101_os8_voc12aug_512x512_40k/SIR_38.py
index 55ea96421c..14c29c7138 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet101_os8_voc12aug_512x512_40k/SIR_38.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet101_os8_voc12aug_512x512_40k/SIR_38.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 512, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_0, bias=self.parameter_1, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet50_os8_cityscapes_769x769_80k/SIR_36.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet50_os8_cityscapes_769x769_80k/SIR_36.py
index 5141193507..4df9ac85da 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet50_os8_cityscapes_769x769_80k/SIR_36.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/isanet_isanet_resnet50_os8_cityscapes_769x769_80k/SIR_36.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 512, 97, 97], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/pfpn_pfpn_resnet101_os8_cityscapes_512x1024_40k/SIR_68.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/pfpn_pfpn_resnet101_os8_cityscapes_512x1024_40k/SIR_68.py
index 686495bd72..3cf1a7cbc9 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/pfpn_pfpn_resnet101_os8_cityscapes_512x1024_40k/SIR_68.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/pfpn_pfpn_resnet101_os8_cityscapes_512x1024_40k/SIR_68.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 256, 256, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_14.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_14.py
index f70d30b572..20942b2da8 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_14.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_14.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 64])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_8, bias=self.parameter_0, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_26.py
index 871ad397eb..9bd2da6952 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_26.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 160])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_1, bias=self.parameter_7, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_38.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_38.py
index 17814f9da3..8badae91bb 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_38.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_38.py
@@ -60,12 +60,12 @@ def forward(
         var_14 = var_7.__matmul__(var_13)
         var_15 = var_14.__mul__(0.1767766952966369)
         var_16 = paddle.nn.functional.activation.softmax(var_15, axis=-1)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_18 = var_17.__matmul__(var_12)
         var_19 = var_18.transpose([0, 2, 1, 3])
         var_20 = var_19.reshape([var_3, var_4, 256])
         var_21 = paddle.nn.functional.common.linear(x=var_20, weight=self.parameter_1, bias=self.parameter_6, name=None)
-        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_22
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_5.py
index 70423da935..de7336ba19 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x1024_160k/SIR_5.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 32])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_2, bias=self.parameter_5, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_14.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_14.py
index a41547d248..aaebab5249 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_14.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_14.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 64])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_3, bias=self.parameter_4, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_26.py
index c65e0a0a0e..2f37860bfa 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_26.py
@@ -105,14 +105,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 160])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_9, bias=self.parameter_4, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_38.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_38.py
index 4bb0c30654..fa74d1f9b1 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_38.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_38.py
@@ -60,12 +60,12 @@ def forward(
         var_14 = var_7.__matmul__(var_13)
         var_15 = var_14.__mul__(0.1767766952966369)
         var_16 = paddle.nn.functional.activation.softmax(var_15, axis=-1)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_18 = var_17.__matmul__(var_12)
         var_19 = var_18.transpose([0, 2, 1, 3])
         var_20 = var_19.reshape([var_3, var_4, 256])
         var_21 = paddle.nn.functional.common.linear(x=var_20, weight=self.parameter_1, bias=self.parameter_0, name=None)
-        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_22
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_5.py
index 60d342e046..d037863d7b 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b0_cityscapes_1024x512_160k/SIR_5.py
@@ -105,14 +105,14 @@ def forward(
         var_23 = var_22.__mul__(0.1767766952966369)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 32])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_7, bias=self.parameter_1, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_106.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_106.py
index 902a7ee875..8d7ad24000 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_106.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_106.py
@@ -60,12 +60,12 @@ def forward(
         var_14 = var_7.__matmul__(var_13)
         var_15 = var_14.__mul__(0.125)
         var_16 = paddle.nn.functional.activation.softmax(var_15, axis=-1)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_18 = var_17.__matmul__(var_12)
         var_19 = var_18.transpose([0, 2, 1, 3])
         var_20 = var_19.reshape([var_3, var_4, 512])
         var_21 = paddle.nn.functional.common.linear(x=var_20, weight=self.parameter_5, bias=self.parameter_4, name=None)
-        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_22
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_18.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_18.py
index 5c3656936a..64f701eea8 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_18.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_18.py
@@ -105,7 +105,7 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
@@ -114,7 +114,7 @@ def forward(
             x=var_28, weight=self.parameter_1, bias=self.parameter_10, name=None
         )
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_38.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_38.py
index dbe50dfc27..462911ce55 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_38.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_38.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 320])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_8, bias=self.parameter_7, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_5.py
index 93d7801e7f..87f2e515ab 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x1024_160k/SIR_5.py
@@ -105,14 +105,14 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 64])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_8, bias=self.parameter_0, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_106.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_106.py
index 319fc60348..4eab99dfce 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_106.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_106.py
@@ -60,12 +60,12 @@ def forward(
         var_14 = var_7.__matmul__(var_13)
         var_15 = var_14.__mul__(0.125)
         var_16 = paddle.nn.functional.activation.softmax(var_15, axis=-1)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_18 = var_17.__matmul__(var_12)
         var_19 = var_18.transpose([0, 2, 1, 3])
         var_20 = var_19.reshape([var_3, var_4, 512])
         var_21 = paddle.nn.functional.common.linear(x=var_20, weight=self.parameter_7, bias=self.parameter_6, name=None)
-        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_22
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_18.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_18.py
index 9727460f65..e1725e0163 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_18.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_18.py
@@ -103,14 +103,14 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 128])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_4, bias=self.parameter_1, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_38.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_38.py
index 08ea52b8a8..e2088a6c13 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_38.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_38.py
@@ -105,14 +105,14 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 320])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_8, bias=self.parameter_4, name=None)
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_5.py
index 0982bd4f1e..cde24b3c99 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segformer_segformer_b3_cityscapes_1024x512_160k/SIR_5.py
@@ -105,7 +105,7 @@ def forward(
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
         var_25 = paddle.nn.functional.common.dropout(
-            var_24, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_24, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
@@ -114,7 +114,7 @@ def forward(
             x=var_28, weight=self.parameter_6, bias=self.parameter_11, name=None
         )
         var_30 = paddle.nn.functional.common.dropout(
-            var_29, p=0.0, axis=None, training=True, mode="upscale_in_train", name=None
+            var_29, p=0.0, axis=None, training=self.training, mode="upscale_in_train", name=None
         )
         return var_30
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_5.py
index f616070009..45408ff145 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_5.py
@@ -51,12 +51,12 @@ def forward(
         var_13 = var_9.matmul(var_12)
         var_14 = var_13.__mul__(0.125)
         var_15 = paddle.nn.functional.activation.softmax(var_14, axis=-1)
-        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_17 = var_16.matmul(var_11)
         var_18 = var_17.transpose((0, 2, 1, 3,))
         var_19 = var_18.reshape((-1, var_3, var_4,))
         var_20 = paddle.nn.functional.common.linear(x=var_19, weight=self.parameter_5, bias=self.parameter_2, name=None)
-        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_21
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_66.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_66.py
index c54c7799a9..e342636112 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_66.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_base_mask_ade20k_512x512_160k/SIR_66.py
@@ -47,12 +47,12 @@ def forward(
         var_13 = var_9.matmul(var_12)
         var_14 = var_13.__mul__(0.125)
         var_15 = paddle.nn.functional.activation.softmax(var_14, axis=-1)
-        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_17 = var_16.matmul(var_11)
         var_18 = var_17.transpose((0, 2, 1, 3,))
         var_19 = var_18.reshape((-1, var_3, var_4,))
         var_20 = paddle.nn.functional.common.linear(x=var_19, weight=self.parameter_1, bias=self.parameter_0, name=None)
-        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_21
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_5.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_5.py
index 43e06f15ea..30ca31cf7d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_5.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_5.py
@@ -51,12 +51,12 @@ def forward(
         var_13 = var_9.matmul(var_12)
         var_14 = var_13.__mul__(0.125)
         var_15 = paddle.nn.functional.activation.softmax(var_14, axis=-1)
-        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_17 = var_16.matmul(var_11)
         var_18 = var_17.transpose((0, 2, 1, 3,))
         var_19 = var_18.reshape((-1, var_3, var_4,))
         var_20 = paddle.nn.functional.common.linear(x=var_19, weight=self.parameter_5, bias=self.parameter_3, name=None)
-        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_21
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
index ff892627a2..7fd3cc2c4f 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
@@ -47,12 +47,12 @@ def forward(
         var_13 = var_9.matmul(var_12)
         var_14 = var_13.__mul__(0.125)
         var_15 = paddle.nn.functional.activation.softmax(var_14, axis=-1)
-        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_17 = var_16.matmul(var_11)
         var_18 = var_17.transpose((0, 2, 1, 3,))
         var_19 = var_18.reshape((-1, var_3, var_4,))
         var_20 = paddle.nn.functional.common.linear(x=var_19, weight=self.parameter_4, bias=self.parameter_0, name=None)
-        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_21
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_small_ade20k_512x512_160k/SIR_128.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_small_ade20k_512x512_160k/SIR_128.py
index b74b065c5f..c0ab74fe32 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_small_ade20k_512x512_160k/SIR_128.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_small_ade20k_512x512_160k/SIR_128.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 192, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
index 833bdd4069..d99d4411bb 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer1000/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [1, 128, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         paddle.seed(33)
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
index d18ba2cc98..a33fd5f3bc 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/DeiT_DeiT_tiny_distilled_patch16_224/SIR_4.py
@@ -46,12 +46,12 @@ def forward(
         var_9 = var_5.matmul(var_8)
         var_10 = var_9.__mul__(0.125)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_7)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((-1, 198, 192,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_1, bias=self.parameter_4, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
index aefcc6ecbd..baa16255b1 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/EfficientNet_EfficientNetB0/SIR_96.py
@@ -20,7 +20,7 @@ def forward(
         var_0,    # (shape: [43, 1280, 7, 7], dtype: paddle.float32, stop_gradient: False)
     ):
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
-        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_2 = paddle.nn.functional.common.dropout(var_1, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Inception_InceptionV4/SIR_40.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Inception_InceptionV4/SIR_40.py
index deb95c8e1b..f843454444 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Inception_InceptionV4/SIR_40.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Inception_InceptionV4/SIR_40.py
@@ -21,7 +21,7 @@ def forward(
     ):
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = paddle.tensor.manipulation.squeeze(var_1, axis=[2, 3])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.2, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
index 1ea1c769af..9f800b9db2 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/MobileViT_MobileViT_XXS/SIR_26.py
@@ -21,7 +21,7 @@ def forward(
     ):
         var_1 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_0, output_size=1, data_format='NCHW', name=None)
         var_2 = var_1.reshape([43, 320])
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/PeleeNet_PeleeNet/SIR_41.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
index c033db0df7..fd5e59b263 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/PeleeNet_PeleeNet/SIR_41.py
@@ -21,7 +21,7 @@ def forward(
     ):
         var_1 = paddle.nn.functional.pooling.avg_pool2d(var_0, kernel_size=[7, 7])
         var_2 = var_1.flatten(1)
-        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=True)
+        var_3 = paddle.nn.functional.common.dropout(var_2, p=0.05, training=self.training)
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_0, bias=self.parameter_1, name=None)
         return var_4
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
index b78dbbbc8d..9de20a32ef 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/ReXNet_ReXNet_3_0/SIR_60.py
@@ -19,7 +19,7 @@ def forward(
         self,
         var_0,    # (shape: [22, 3840, 1, 1], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.2, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_1, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_3 = var_2.squeeze(axis=-1)
         var_4 = var_3.squeeze(axis=-1)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
index b0cf1d2222..f56fa5a5d5 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/SqueezeNet_SqueezeNet1_0/SIR_0.py
@@ -280,7 +280,7 @@ def forward(
         var_59 = paddle.nn.functional.conv._conv_nd(var_56, self.parameter_2, bias=self.parameter_30, stride=[1, 1], padding=[1, 1], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_60 = paddle.nn.functional.activation.relu(var_59)
         var_61 = paddle.tensor.manipulation.concat([var_58, var_60], axis=1)
-        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_62 = paddle.nn.functional.common.dropout(var_61, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_63 = paddle.nn.functional.conv._conv_nd(var_62, self.parameter_29, bias=self.parameter_44, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_64 = paddle.nn.functional.activation.relu(var_63)
         var_65 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_64, output_size=1, data_format='NCHW', name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Twins_alt_gvt_base/SIR_84.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Twins_alt_gvt_base/SIR_84.py
index c7007a83f7..ae22189bd5 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Twins_alt_gvt_base/SIR_84.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Twins_alt_gvt_base/SIR_84.py
@@ -31,7 +31,7 @@ def forward(
         var_2 = var_1.flatten(2)
         var_3 = var_2.transpose([0, 2, 1])
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[96], weight=self.parameter_3, bias=self.parameter_2, epsilon=1e-05)
-        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_5 = paddle.nn.functional.common.dropout(var_4, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_5
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Xception_Xception65_deeplab/SIR_35.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
index bc58eb87f0..7a7c614ff3 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Clas_cases/Xception_Xception65_deeplab/SIR_35.py
@@ -19,7 +19,7 @@ def forward(
         self,
         var_0,    # (shape: [22, 2048, 10, 10], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=True, mode='downscale_in_infer', name=None)
+        var_1 = paddle.nn.functional.common.dropout(var_0, p=0.5, axis=None, training=self.training, mode='downscale_in_infer', name=None)
         var_2 = paddle.nn.functional.pooling.adaptive_avg_pool2d(var_1, output_size=1, data_format='NCHW', name=None)
         var_3 = paddle.tensor.manipulation.squeeze(var_2, axis=[2, 3])
         var_4 = paddle.nn.functional.common.linear(x=var_3, weight=self.parameter_1, bias=self.parameter_0, name=None)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
index 3659ee8a94..dd50590b4c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/faster_rcnn_faster_rcnn_swin_tiny_fpn_1x_coco/SIR_3.py
@@ -35,7 +35,7 @@ def forward(
         var_6 = var_5.reshape([-1, 96, 160, 240])
         var_7 = var_6.flatten(2)
         var_8 = var_7.transpose([0, 2, 1])
-        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_9
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
index 87e5069c42..e1da098ce6 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/smalldet_ppyoloe_plus_sod_crn_l_80e_coco/SIR_127.py
@@ -44,14 +44,14 @@ def forward(
         var_0,    # (shape: [1, 361, 1024], dtype: paddle.float32, stop_gradient: False)
         var_1,    # (shape: [1, 361, 1024], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_2 = paddle.nn.functional.common.dropout(var_0, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_2 = paddle.nn.functional.common.dropout(var_0, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_3 = var_1.__add__(var_2)
         var_4 = paddle.nn.functional.norm.layer_norm(var_3, normalized_shape=[1024], weight=self.parameter_6, bias=self.parameter_7, epsilon=1e-05)
         var_5 = paddle.nn.functional.common.linear(x=var_4, weight=self.parameter_4, bias=self.parameter_5, name=None)
         var_6 = paddle.nn.functional.activation.gelu(var_5)
-        var_7 = paddle.nn.functional.common.dropout(var_6, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_7 = paddle.nn.functional.common.dropout(var_6, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_8 = paddle.nn.functional.common.linear(x=var_7, weight=self.parameter_1, bias=self.parameter_0, name=None)
-        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.1, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_9 = paddle.nn.functional.common.dropout(var_8, p=0.1, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_10 = var_4.__add__(var_9)
         var_11 = paddle.nn.functional.norm.layer_norm(var_10, normalized_shape=[1024], weight=self.parameter_2, bias=self.parameter_3, epsilon=1e-05)
         return var_11
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
index 610c4dec8b..057061838d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Det_cases/vitdet_ppyoloe_vit_base_csppan_cae_36e_coco/SIR_6.py
@@ -60,12 +60,12 @@ def forward(
         var_15 = var_11.matmul(var_14)
         var_16 = var_15.__mul__(0.125)
         var_17 = paddle.nn.functional.activation.softmax(var_16, axis=-1)
-        var_18 = paddle.nn.functional.common.dropout(var_17, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_18 = paddle.nn.functional.common.dropout(var_17, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_19 = var_18.matmul(var_13)
         var_20 = var_19.transpose((0, 2, 1, 3,))
         var_21 = var_20.reshape((-1, var_3, var_4,))
         var_22 = paddle.nn.functional.common.linear(x=var_21, weight=self.parameter_5, bias=self.parameter_0, name=None)
-        var_23 = paddle.nn.functional.common.dropout(var_22, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_23 = paddle.nn.functional.common.dropout(var_22, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_24 = self.parameter_3.__mul__(var_23)
         return var_24
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_43.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_43.py
index bac371baad..fa9c036d0b 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_43.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_43.py
@@ -48,12 +48,12 @@ def forward(
         var_11 = var_7.matmul(var_10)
         var_12 = var_11.__add__(var_1)
         var_13 = paddle.nn.functional.activation.softmax(var_12, axis=-1)
-        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_14 = paddle.nn.functional.common.dropout(var_13, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_15 = var_14.matmul(var_9)
         var_16 = var_15.transpose((0, 2, 1, 3,))
         var_17 = var_16.reshape((0, -1, 128,))
         var_18 = paddle.nn.functional.common.linear(x=var_17, weight=self.parameter_5, bias=self.parameter_2, name=None)
-        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_19 = paddle.nn.functional.common.dropout(var_18, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_19
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_57.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_57.py
index 440c546337..dd2de38b2c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_57.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Ocr_cases/rec_rec_svtrnet/SIR_57.py
@@ -46,12 +46,12 @@ def forward(
         var_9 = var_7.transpose((0, 1, 3, 2,))
         var_10 = var_6.matmul(var_9)
         var_11 = paddle.nn.functional.activation.softmax(var_10, axis=-1)
-        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_12 = paddle.nn.functional.common.dropout(var_11, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_13 = var_12.matmul(var_8)
         var_14 = var_13.transpose((0, 2, 1, 3,))
         var_15 = var_14.reshape((0, -1, 128,))
         var_16 = paddle.nn.functional.common.linear(x=var_15, weight=self.parameter_0, bias=self.parameter_5, name=None)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_17
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/danet_danet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/danet_danet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
index c239162788..eda34ec0b0 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/danet_danet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/danet_danet_resnet101_os8_cityscapes_1024x512_80k/SIR_34.py
@@ -38,13 +38,13 @@ def forward(
         var_2,    # (shape: [1, 2048, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_0, bias=self.parameter_1, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_5, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_5, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_3, bias=self.parameter_2, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
index ae9e67a190..74540c8c3c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_40.py
@@ -11,7 +11,7 @@ def forward(
         self,
         var_0,    # (shape: [1, 128, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         return var_1
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
index 19f79d625b..0b331ed44e 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/enet_enet_cityscapes_1024x512_80k/SIR_46.py
@@ -12,7 +12,7 @@ def forward(
         var_0,    # (shape: [1, 128, 64, 128], dtype: paddle.float32, stop_gradient: False)
         var_1,    # (shape: [1, 128, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_2 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_3 = var_1.__add__(var_2)
         return var_3
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
index 0050a41c7a..8458707449 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
@@ -19,7 +19,7 @@ def forward(
     ):
         var_3 = paddle.nn.functional.common.interpolate(var_0, scale_factor=2, mode='bilinear', align_corners=True)
         var_4 = paddle.tensor.manipulation.concat([var_1, var_3], axis=1)
-        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=True, data_format='NCHW', name=None)
+        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=self.training, data_format='NCHW', name=None)
         var_6 = paddle.nn.functional.conv._conv_nd(var_5, self.parameter_0, bias=None, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_7 = paddle.nn.functional.common.interpolate(var_6, scale_factor=2, mode='bilinear', align_corners=True)
         var_8 = paddle.nn.functional.common.interpolate(var_2, scale_factor=2, mode='bilinear', align_corners=True)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_18.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_18.py
index 591daf7a0d..7f3eac8691 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_18.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_18.py
@@ -83,12 +83,12 @@ def forward(
         var_22 = var_9.__matmul__(var_21)
         var_23 = var_22.__mul__(0.125)
         var_24 = paddle.nn.functional.activation.softmax(var_23, axis=-1)
-        var_25 = paddle.nn.functional.common.dropout(var_24, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_25 = paddle.nn.functional.common.dropout(var_24, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_26 = var_25.__matmul__(var_20)
         var_27 = var_26.transpose([0, 2, 1, 3])
         var_28 = var_27.reshape([var_5, var_6, 128])
         var_29 = paddle.nn.functional.common.linear(x=var_28, weight=self.parameter_8, bias=self.parameter_6, name=None)
-        var_30 = paddle.nn.functional.common.dropout(var_29, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_30 = paddle.nn.functional.common.dropout(var_29, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_30
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_66.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_66.py
index 68223854c3..63755e893c 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_66.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segformer_segformer_b2_cityscapes_1024x1024_160k/SIR_66.py
@@ -59,12 +59,12 @@ def forward(
         var_14 = var_7.__matmul__(var_13)
         var_15 = var_14.__mul__(0.125)
         var_16 = paddle.nn.functional.activation.softmax(var_15, axis=-1)
-        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_17 = paddle.nn.functional.common.dropout(var_16, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_18 = var_17.__matmul__(var_12)
         var_19 = var_18.transpose([0, 2, 1, 3])
         var_20 = var_19.reshape([var_3, var_4, 512])
         var_21 = paddle.nn.functional.common.linear(x=var_20, weight=self.parameter_5, bias=self.parameter_2, name=None)
-        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_22 = paddle.nn.functional.common.dropout(var_21, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_22
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
index 14c6818504..c243a92e10 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/segmenter_segmenter_vit_small_mask_ade20k_512x512_160k/SIR_66.py
@@ -46,12 +46,12 @@ def forward(
         var_13 = var_9.matmul(var_12)
         var_14 = var_13.__mul__(0.125)
         var_15 = paddle.nn.functional.activation.softmax(var_14, axis=-1)
-        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_16 = paddle.nn.functional.common.dropout(var_15, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         var_17 = var_16.matmul(var_11)
         var_18 = var_17.transpose((0, 2, 1, 3,))
         var_19 = var_18.reshape((-1, var_3, var_4,))
         var_20 = paddle.nn.functional.common.linear(x=var_19, weight=self.parameter_4, bias=self.parameter_2, name=None)
-        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=True, mode='upscale_in_train', name=None)
+        var_21 = paddle.nn.functional.common.dropout(var_20, p=0.0, axis=None, training=self.training, mode='upscale_in_train', name=None)
         return var_21
 
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
index 65c4e9bcdb..efe1faa64d 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer160/Seg_cases/topformer_topformer_tiny_ade20k_512x512_160k/SIR_126.py
@@ -19,7 +19,7 @@ def forward(
         self,
         var_0,    # (shape: [1, 128, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
-        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_1 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_2 = paddle.nn.functional.conv._conv_nd(var_1, self.parameter_0, bias=self.parameter_1, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_2
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
index 27561ee309..eef564a138 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
@@ -38,13 +38,13 @@ def forward(
         var_2,    # (shape: [1, 2048, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_2, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_5, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
index a9f920a83e..8b07aef637 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
@@ -38,13 +38,13 @@ def forward(
         var_2,    # (shape: [1, 2048, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_5, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_2, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
index 0050a41c7a..8458707449 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
@@ -19,7 +19,7 @@ def forward(
     ):
         var_3 = paddle.nn.functional.common.interpolate(var_0, scale_factor=2, mode='bilinear', align_corners=True)
         var_4 = paddle.tensor.manipulation.concat([var_1, var_3], axis=1)
-        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=True, data_format='NCHW', name=None)
+        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=self.training, data_format='NCHW', name=None)
         var_6 = paddle.nn.functional.conv._conv_nd(var_5, self.parameter_0, bias=None, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_7 = paddle.nn.functional.common.interpolate(var_6, scale_factor=2, mode='bilinear', align_corners=True)
         var_8 = paddle.nn.functional.common.interpolate(var_2, scale_factor=2, mode='bilinear', align_corners=True)
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
index 27561ee309..eef564a138 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_cityscapes_1024x512_80k/SIR_34.py
@@ -38,13 +38,13 @@ def forward(
         var_2,    # (shape: [1, 2048, 64, 128], dtype: paddle.float32, stop_gradient: False)
     ):
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_2, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_5, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
index a9f920a83e..8b07aef637 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/danet_danet_resnet50_os8_voc12aug_512x512_40k/SIR_34.py
@@ -38,13 +38,13 @@ def forward(
         var_2,    # (shape: [1, 2048, 64, 64], dtype: paddle.float32, stop_gradient: False)
     ):
         var_3 = var_0.__add__(var_1)
-        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=True, data_format='NCHW', name=None)
+        var_4 = paddle.nn.functional.common.dropout2d(var_3, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_5 = paddle.nn.functional.conv._conv_nd(var_4, self.parameter_5, bias=self.parameter_0, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=True, data_format='NCHW', name=None)
+        var_6 = paddle.nn.functional.common.dropout2d(var_1, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_7 = paddle.nn.functional.conv._conv_nd(var_6, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=True, data_format='NCHW', name=None)
+        var_8 = paddle.nn.functional.common.dropout2d(var_0, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_9 = paddle.nn.functional.conv._conv_nd(var_8, self.parameter_4, bias=self.parameter_3, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
-        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=True, data_format='NCHW', name=None)
+        var_10 = paddle.nn.functional.common.dropout2d(var_2, p=0.1, training=self.training, data_format='NCHW', name=None)
         var_11 = paddle.nn.functional.conv._conv_nd(var_10, self.parameter_1, bias=self.parameter_2, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         return var_5, var_7, var_9, var_11
 
diff --git a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
index 0050a41c7a..8458707449 100644
--- a/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
+++ b/framework/e2e/PaddleLT_new/layercase/sublayer_search90plusplus/Seg_cases/espnet_espnet_cityscapes_1024x512_120k/SIR_143.py
@@ -19,7 +19,7 @@ def forward(
     ):
         var_3 = paddle.nn.functional.common.interpolate(var_0, scale_factor=2, mode='bilinear', align_corners=True)
         var_4 = paddle.tensor.manipulation.concat([var_1, var_3], axis=1)
-        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=True, data_format='NCHW', name=None)
+        var_5 = paddle.nn.functional.common.dropout2d(var_4, p=0.0, training=self.training, data_format='NCHW', name=None)
         var_6 = paddle.nn.functional.conv._conv_nd(var_5, self.parameter_0, bias=None, stride=[1, 1], padding=[0, 0], padding_algorithm='EXPLICIT', dilation=[1, 1], groups=1, data_format='NCHW', channel_dim=1, op_type='conv2d', use_cudnn=True)
         var_7 = paddle.nn.functional.common.interpolate(var_6, scale_factor=2, mode='bilinear', align_corners=True)
         var_8 = paddle.nn.functional.common.interpolate(var_2, scale_factor=2, mode='bilinear', align_corners=True)
diff --git a/framework/e2e/PaddleLT_new/layertest.py b/framework/e2e/PaddleLT_new/layertest.py
index 5a6ea908d1..1587b543bc 100644
--- a/framework/e2e/PaddleLT_new/layertest.py
+++ b/framework/e2e/PaddleLT_new/layertest.py
@@ -10,7 +10,7 @@
 import traceback
 
 # from engine.engine_map import engine_map
-from strategy.compare import base_compare
+from strategy.compare import base_compare, infer_compare
 from tools.yaml_loader import YamlLoader
 from tools.logger import Logger
 from tools.res_save import save_tensor, load_tensor, save_pickle
@@ -59,7 +59,7 @@ def del_core_dump(self):
                 # 如果删除过程中发生错误（比如文件不存在或没有权限），则打印错误信息
                 self.logger.get_log().warning(f"Error deleting {filepath}: {e.strerror}")
 
-    def _single_run(self, testing, layerfile, device_place_id=0):
+    def _single_run(self, testing, layerfile, device_place_id=0, upstream_net=None):
         """
         单次执行器测试
         :param testing: 'dy_train', 'dy_eval'...
@@ -78,7 +78,10 @@ def _single_run(self, testing, layerfile, device_place_id=0):
                     self.logger.get_log().info(f"testing engine has been covered. Real engine is: {engine}")
 
         layer_test = engine_map[engine](
-            testing=self.testings.get(testing), layerfile=layerfile, device_place_id=device_place_id
+            testing=self.testings.get(testing),
+            layerfile=layerfile,
+            device_place_id=device_place_id,
+            upstream_net=upstream_net,
         )
         res = getattr(layer_test, engine)()
         return res
@@ -90,14 +93,20 @@ def _case_run(self):
         exc_func = 0
         exc = 0
         res_dict = {}
+        net = None
         compare_res_list = []
         self.logger.get_log().info("测试case名称: {}".format(self.title))
         fail_testing_list = []
         for testing in self.testings_list:
             try:
                 self.logger.get_log().info("测试执行器: {}".format(testing))
-                res = self._single_run(testing=testing, layerfile=self.layerfile, device_place_id=self.device_place_id)
-                res_dict[testing] = res
+                if self.testings.get(testing).get("use_upstream_net_instance", "False") == "False":
+                    net = None
+                res = self._single_run(
+                    testing=testing, layerfile=self.layerfile, device_place_id=self.device_place_id, upstream_net=net
+                )
+                res_dict[testing] = res["res"]
+                net = res.get("net", None)
                 if os.environ.get("PLT_SAVE_GT") == "True":  # 开启gt保存
                     gt_path = os.path.join("plt_gt", os.environ.get("PLT_SET_DEVICE"), testing)
                     if not os.path.exists(gt_path):
@@ -154,7 +163,11 @@ def _case_run(self):
                         compare_res_list.append(tmp)
                 else:
                     precision = comparing.get("precision")
-                    compare_res = base_compare(
+                    if comparing.get("compare_method", "base_compare") == "infer_compare":
+                        compare_methon = infer_compare
+                    else:
+                        compare_methon = base_compare
+                    compare_res = compare_methon(
                         result=result,
                         expect=expect,
                         res_name=latest,
diff --git a/framework/e2e/PaddleLT_new/strategy/compare.py b/framework/e2e/PaddleLT_new/strategy/compare.py
index 467949ede9..7f33174387 100644
--- a/framework/e2e/PaddleLT_new/strategy/compare.py
+++ b/framework/e2e/PaddleLT_new/strategy/compare.py
@@ -8,10 +8,13 @@
 
 import os
 import json
-import logging
+
+# import logging
 import traceback
 import numpy as np
 
+from tools.logger import Logger
+
 framework = ""
 if os.environ.get("FRAMEWORK") == "paddle":
     import paddle
@@ -37,7 +40,13 @@ def base_compare(result, expect, res_name, exp_name, logger, delta=1e-10, rtol=1
     if isinstance(expect, str):
         raise Exception("expect is exception !!!")
 
-    if isinstance(expect, eval(f"{framework}.Tensor")) or isinstance(expect, np.ndarray):
+    if expect is None or result is None:
+        if expect is None:
+            Logger("PLT_compare").get_log().info(f"{exp_name} 结果为None, 所以跳过 {exp_name} 和 {res_name} 精度对比")
+        if result is None:
+            Logger("PLT_compare").get_log().info(f"{res_name} 结果为None, 所以跳过 {exp_name} 和 {res_name} 精度对比")
+        pass
+    elif isinstance(expect, eval(f"{framework}.Tensor")) or isinstance(expect, np.ndarray):
         if isinstance(result, eval(f"{framework}.Tensor")):
             if framework == "torch":
                 result = result.detach().numpy()
@@ -92,16 +101,19 @@ def base_compare(result, expect, res_name, exp_name, logger, delta=1e-10, rtol=1
                 )
         else:
             for k, v in expect.items():
-                base_compare(
-                    result=result[k],
-                    expect=expect[k],
-                    res_name=res_name + "[{}]".format(str(k)),
-                    exp_name=exp_name + "[{}]".format(str(k)),
-                    logger=logger,
-                    delta=delta,
-                    rtol=rtol,
-                    exc_dict=exc_dict,
-                )
+                if k in result:
+                    base_compare(
+                        result=result[k],
+                        expect=expect[k],
+                        res_name=res_name + "[{}]".format(str(k)),
+                        exp_name=exp_name + "[{}]".format(str(k)),
+                        logger=logger,
+                        delta=delta,
+                        rtol=rtol,
+                        exc_dict=exc_dict,
+                    )
+                else:
+                    Logger("PLT_compare").get_log().info(f"{exp_name} 有 {k}, 但是 {res_name} 没有 {k}, 所以跳过 {k} 精度对比")
     elif isinstance(expect, list) or isinstance(expect, tuple):
         for i, element in enumerate(expect):
             if isinstance(result, (np.generic, np.ndarray)) or isinstance(result, eval(f"{framework}.Tensor")):
@@ -130,14 +142,49 @@ def base_compare(result, expect, res_name, exp_name, logger, delta=1e-10, rtol=1
                 )
     elif isinstance(expect, (bool, int, float)):
         assert expect == result
-    elif expect is None:
-        pass
     else:
         raise Exception("expect is unknown data struction in compare_tool!!!")
 
     return exc_dict
 
 
+def infer_compare(result, expect, res_name, exp_name, logger, delta=1e-10, rtol=1e-10, exc_dict={}):
+    """
+    比较函数
+    :param result: 待测值
+    :param expect: 基线值
+    :param delta: 误差值
+    :param rtol: 相对误差
+    :return:
+    """
+    # 去除反向结果的数据
+    forward_handled_result = {"logit": []}
+    forward_handled_expect = {"logit": []}
+
+    # 去除非tensor数值的影响
+    if isinstance(expect["logit"], (tuple, list)):
+        for item in expect["logit"]:
+            if not isinstance(item, (int, bool, float)):
+                forward_handled_expect["logit"].append(item)
+
+    if isinstance(result["logit"], (tuple, list)):
+        for item in result["logit"]:
+            if not isinstance(item, (int, bool, float)):
+                forward_handled_result["logit"].append(item)
+
+    exc_dict = base_compare(
+        result=forward_handled_result,
+        expect=forward_handled_expect,
+        res_name=res_name,
+        exp_name=exp_name,
+        logger=logger,
+        delta=delta,
+        rtol=rtol,
+        exc_dict=exc_dict,
+    )
+    return exc_dict
+
+
 def perf_compare_legacy(baseline, latest):
     """
     比较函数
@@ -353,8 +400,6 @@ def perf_compare_kernel_dict(
 
 
 if __name__ == "__main__":
-    from tools.logger import Logger
-
     result = {
         "logit": [paddle.to_tensor([1.0]), paddle.to_tensor([1.0])],
         "data_grad": [paddle.to_tensor([0.0]), paddle.to_tensor([0.0])],
diff --git a/framework/e2e/PaddleLT_new/yaml/dy^dy2st_train_static_inputspec^export_st_inputspec^ppinfer_new_exc_pir.yml b/framework/e2e/PaddleLT_new/yaml/dy^dy2st_train_static_inputspec^export_st_inputspec^ppinfer_new_exc_pir.yml
new file mode 100644
index 0000000000..5e71b204c3
--- /dev/null
+++ b/framework/e2e/PaddleLT_new/yaml/dy^dy2st_train_static_inputspec^export_st_inputspec^ppinfer_new_exc_pir.yml
@@ -0,0 +1,53 @@
+testings:
+  dy_train:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 20
+
+  dy2st_train_static_inputspec:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 20
+    return_net_instance: "True"  # 测试engine会返回模型实例
+
+  jit_save_static_inputspec:
+    use_upstream_net_instance: "True"  # 获取上游模型实例而不是重新构建模型实例
+    model_dtype: "float32"
+
+  paddle_infer_new_exc_pir:
+    jit_save_type: "jit_save_static_inputspec"
+
+compare:
+  -
+    baseline: 'dy_train'
+    latest: 'dy2st_train_static_inputspec'
+    compare_method: "base_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
+  -
+    baseline: 'dy_train'
+    latest: 'paddle_infer_new_exc_pir'
+    compare_method: "infer_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
+  -
+    baseline: 'dy2st_train_static_inputspec'
+    latest: 'paddle_infer_new_exc_pir'
+    compare_method: "infer_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
diff --git a/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train^export_cinn_st_inputspec^ppinfer_new_exc_pir.yml b/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train^export_cinn_st_inputspec^ppinfer_new_exc_pir.yml
new file mode 100644
index 0000000000..a804cd2b37
--- /dev/null
+++ b/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train^export_cinn_st_inputspec^ppinfer_new_exc_pir.yml
@@ -0,0 +1,53 @@
+testings:
+  dy_train:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 20
+
+  dy2st_train_cinn:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 20
+    return_net_instance: "True"  # 测试engine会返回模型实例
+
+  jit_save_cinn_static_inputspec:
+    use_upstream_net_instance: "True"  # 获取上游模型实例而不是重新构建模型实例
+    model_dtype: "float32"
+
+  paddle_infer_new_exc_pir:
+    jit_save_type: "jit_save_cinn_static_inputspec"
+
+compare:
+  -
+    baseline: 'dy_train'
+    latest: 'dy2st_train_cinn'
+    compare_method: "base_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
+  -
+    baseline: 'dy_train'
+    latest: 'paddle_infer_new_exc_pir'
+    compare_method: "infer_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
+  -
+    baseline: 'dy2st_train_cinn'
+    latest: 'paddle_infer_new_exc_pir'
+    compare_method: "infer_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001
diff --git a/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train_inputspec_benchmark.yml b/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train_inputspec_benchmark.yml
new file mode 100644
index 0000000000..b849e9926a
--- /dev/null
+++ b/framework/e2e/PaddleLT_new/yaml/dy^dy2stcinn_train_inputspec_benchmark.yml
@@ -0,0 +1,28 @@
+# 暂时没有开发dy2st_train_cinn_inputspec_perf
+testings:
+  dy_train_perf:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 1
+
+  dy2st_train_cinn_inputspec_perf:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 1
+
+compare:
+  -
+    baseline: 'dy_train_perf'
+    latest: 'dy2st_train_cinn_inputspec_perf'
diff --git a/framework/e2e/PaddleLT_new/yaml/dy^dy_train^export_st_inputspec^ppinfer_new_exc_pir.yml b/framework/e2e/PaddleLT_new/yaml/dy^dy_train^export_st_inputspec^ppinfer_new_exc_pir.yml
new file mode 100644
index 0000000000..5a089b8c73
--- /dev/null
+++ b/framework/e2e/PaddleLT_new/yaml/dy^dy_train^export_st_inputspec^ppinfer_new_exc_pir.yml
@@ -0,0 +1,33 @@
+testings:
+  dy_train:
+    model_dtype: "float32"
+    Loss:
+      loss_name: "diy.loss.diy_loss.mean_loss"
+    optimizer:
+      optimizer_name: "diy.optimizer.diy_opt.naive_opt"
+      params:
+        opt_api: "paddle.optimizer.SGD"
+        learning_rate: 0.00001
+    step: 20
+    return_net_instance: "True"  # 测试engine会返回模型实例
+
+  dy_eval:
+    use_upstream_net_instance: "True"  # 获取上游模型实例而不是重新构建模型实例
+    model_dtype: "float32"
+    return_net_instance: "True"  # 测试engine会返回模型实例
+
+  jit_save_static_inputspec:
+    use_upstream_net_instance: "True"  # 获取上游模型实例而不是重新构建模型实例
+    model_dtype: "float32"
+
+  paddle_infer_new_exc_pir:
+    jit_save_type: "jit_save_static_inputspec"
+
+compare:
+  -
+    baseline: 'dy_eval'
+    latest: 'paddle_infer_new_exc_pir'
+    # compare_method: "infer_compare"
+    precision:
+      delta: 0.00001
+      rtol: 0.000001