diff --git a/fluid/PaddleCV/video/models/model.py b/fluid/PaddleCV/video/models/model.py
index 54c454eb0232dc0e7c5061c7d30cb53d58a0e13e..44f888ef39ef1445fae0a6f0e3622002bf6cb66a 100755
--- a/fluid/PaddleCV/video/models/model.py
+++ b/fluid/PaddleCV/video/models/model.py
@@ -143,6 +143,7 @@ class ModelBase(object):
         return path
 
     def load_pretrain_params(self, exe, pretrain, prog, place):
+        logger.info("Load pretrain weights from {}".format(pretrain))
         fluid.io.load_params(exe, pretrain, main_program=prog)
 
     def get_config_from_sec(self, sec, item, default=None):
diff --git a/fluid/PaddleCV/video/models/stnet/stnet.py b/fluid/PaddleCV/video/models/stnet/stnet.py
index 0d710ee7edbd98a70a741370a3c200dc92e81490..e20ad0bd2adf21d6920a7660f86ff4a026b74060 100644
--- a/fluid/PaddleCV/video/models/stnet/stnet.py
+++ b/fluid/PaddleCV/video/models/stnet/stnet.py
@@ -17,6 +17,9 @@ import paddle.fluid as fluid
 from ..model import ModelBase
 from .stnet_res_model import StNet_ResNet
 
+import logging
+logger = logging.getLogger(__name__)
+
 __all__ = ["STNET"]
 
 
@@ -131,6 +134,7 @@ class STNET(ModelBase):
                 return isinstance(var, fluid.framework.Parameter) and (not ("fc_0" in var.name)) \
                     and (not ("batch_norm" in var.name)) and (not ("xception" in var.name)) and (not ("conv3d" in var.name))
 
+        logger.info("Load pretrain weights from {}, exclude fc, batch_norm, xception, conv3d layers.".format(pretrain))
         vars = filter(is_parameter, prog.list_vars())
         fluid.io.load_vars(exe, pretrain, vars=vars, main_program=prog)
 
diff --git a/fluid/PaddleCV/video/models/tsn/tsn.py b/fluid/PaddleCV/video/models/tsn/tsn.py
index be145858ed6e9c359a36a4fadbd0b2e7d5ad2e51..5bc8aba3886df138fc5111965b344d47325063cd 100644
--- a/fluid/PaddleCV/video/models/tsn/tsn.py
+++ b/fluid/PaddleCV/video/models/tsn/tsn.py
@@ -18,6 +18,9 @@ from paddle.fluid import ParamAttr
 from ..model import ModelBase
 from .tsn_res_model import TSN_ResNet
 
+import logging
+logger = logging.getLogger(__name__)
+
 __all__ = ["TSN"]
 
 
@@ -133,6 +136,7 @@ class TSN(ModelBase):
         def is_parameter(var):
             return isinstance(var, fluid.framework.Parameter) and (not ("fc_0" in var.name))
 
+        logger.info("Load pretrain weights from {}, exclude fc layer.".format(pretrain))
         vars = filter(is_parameter, prog.list_vars())
         fluid.io.load_vars(exe, pretrain, vars=vars, main_program=prog)