diff --git a/configs/pspnet.yaml b/configs/pspnet.yaml
index 7621ab9b917bdbbe5bde51edc5006cde354919da..10ad29497e61d5581267059a2ab501a9fa9f7f5c 100644
--- a/configs/pspnet.yaml
+++ b/configs/pspnet.yaml
@@ -10,18 +10,6 @@ AUG:
     MIN_SCALE_FACTOR: 0.5  # for stepscaling
     SCALE_STEP_SIZE: 0.25  # for stepscaling
     MIRROR: True
-    RICH_CROP:
-        ENABLE: False
-        ASPECT_RATIO: 0.33
-        BLUR: True
-        BLUR_RATIO: 0.1
-        FLIP: True
-        FLIP_RATIO: 0.2
-        MAX_ROTATION: 15
-        MIN_AREA_RATIO: 0.5
-        BRIGHTNESS_JITTER_RATIO: 0.5
-        CONTRAST_JITTER_RATIO: 0.5
-        SATURATION_JITTER_RATIO: 0.5
 BATCH_SIZE: 4
 DATASET:
     DATA_DIR: "./dataset/cityscapes/"
@@ -38,11 +26,10 @@ MODEL:
     MODEL_NAME: "pspnet"
     DEFAULT_NORM_TYPE: "bn"
 TEST:
-    TEST_MODEL: "pretrained_model/pspnet50_ADE20K/" #pspnet101_cityscapes
+    TEST_MODEL: "pretrained_model/pspnet50_ADE20K/"
 TRAIN:
     MODEL_SAVE_DIR: "snapshots/cityscape_pspnet50/"
-    PRETRAINED_MODEL: u"pretrained_model/pspnet50_ADE20K/"
-    RESUME: False
+    PRETRAINED_MODEL_DIR: u"pretrained_model/pspnet50_ADE20K/"
     SNAPSHOT_EPOCH: 10
 SOLVER:
     LR: 0.001
diff --git a/pdseg/models/modeling/pspnet.py b/pdseg/models/modeling/pspnet.py
index 02a1c5a4d89212af0b8b7253e2e0569d91bbb172..471308616adf8fdd537d9eeaee9bc75f54b0b937 100644
--- a/pdseg/models/modeling/pspnet.py
+++ b/pdseg/models/modeling/pspnet.py
@@ -29,7 +29,7 @@ def get_logit_interp(input, num_classes, out_shape, name="logit"):
         logit_interp = fluid.layers.resize_bilinear(
                     logit, 
                     out_shape=out_shape,
-                    name='logit_interp') 
+                    name=name+'_interp') 
     return logit_interp
 
 
@@ -42,7 +42,7 @@ def psp_module(input, out_features):
     cat_layers = []
     sizes = (1,2,3,6)
     for size in sizes:
-        psp_name = "psp_conv" + str(size)
+        psp_name = "psp" + str(size)
         with scope(psp_name):
             pool = fluid.layers.adaptive_pool2d(input, 
                     pool_size=[size, size], 
@@ -60,7 +60,7 @@ def psp_module(input, out_features):
     cat_layers = [input] + cat_layers[::-1]
     cat = fluid.layers.concat(cat_layers, axis=1, name='psp_cat')
 
-    psp_end_name = "psp_conv_end"
+    psp_end_name = "psp_end"
     with scope(psp_end_name):
         data = conv(cat, 
                     out_features,