fix according to comments

Author: juncaipeng

deploy/python/infer.py

@@ -95,7 +95,7 @@ def __init__(self, args):
                     use_static=False,
                     use_calib_mode=False)
                 min_input_shape = {"x": [1, 3, 100, 100]}
-                max_input_shape = {"x": [1, 3, 2000, 2000]}
+                max_input_shape = {"x": [1, 3, 2000, 3000]}
                 opt_input_shape = {"x": [1, 3, 192, 192]}
                 pred_cfg.set_trt_dynamic_shape_info(
                     min_input_shape, max_input_shape, opt_input_shape)

paddleseg/models/backbones/hrnet.py

@@ -360,7 +360,7 @@ def __init__(self,
                 reduction_ratio=16,
                 name=name + '_fc')
 
-        self.add = layers.add()
+        self.add = layers.Add()
         self.relu = layers.Activation("relu")
 
     def forward(self, x):
@@ -422,7 +422,7 @@ def __init__(self,
                 reduction_ratio=16,
                 name=name + '_fc')
 
-        self.add = layers.add()
+        self.add = layers.Add()
         self.relu = layers.Activation("relu")
 
     def forward(self, x):

paddleseg/models/backbones/resnet_vd.py

@@ -121,7 +121,7 @@ def __init__(self,
 
         self.shortcut = shortcut
         # NOTE: Use the wrap layer for quantization training
-        self.add = layers.add()
+        self.add = layers.Add()
         self.relu = layers.Activation(act="relu")
 
     def forward(self, inputs):
@@ -177,7 +177,7 @@ def __init__(self,
         self.shortcut = shortcut
         self.dilation = dilation
         self.data_format = data_format
-        self.add = layers.add()
+        self.add = layers.Add()
         self.relu = layers.Activation(act="relu")
 
     def forward(self, inputs):

paddleseg/models/bisenet.py

@@ -131,12 +131,13 @@ def __init__(self, in_dim, out_dim):
         self.bn = layers.SyncBatchNorm(in_dim)
 
         self.conv_1x1 = layers.ConvBNReLU(in_dim, out_dim, 1)
+        self.add = layers.Add()
         self.conv_3x3 = nn.Conv2D(out_dim, out_dim, 3, 1, 1)
 
     def forward(self, x):
         gap = self.gap(x)
         bn = self.bn(gap)
-        conv1 = self.conv_1x1(bn) + x
+        conv1 = self.add(self.conv_1x1(bn), x)
         return self.conv_3x3(conv1)
 
 
@@ -152,9 +153,10 @@ def __init__(self, in_dim, out_dim, expand):
             layers.ConvBNReLU(in_dim, in_dim, 3),
             layers.DepthwiseConvBN(in_dim, expand_dim, 3),
             layers.ConvBN(expand_dim, out_dim, 1))
+        self.relu = layers.Activation("relu")
 
     def forward(self, x):
-        return F.relu(self.conv(x) + x)
+        return self.relu(self.conv(x) + x)
 
 
 class GatherAndExpansionLayer2(nn.Layer):
@@ -175,8 +177,10 @@ def __init__(self, in_dim, out_dim, expand):
             layers.DepthwiseConvBN(in_dim, in_dim, 3, stride=2),
             layers.ConvBN(in_dim, out_dim, 1))
 
+        self.relu = layers.Activation("relu")
+
     def forward(self, x):
-        return F.relu(self.branch_1(x) + self.branch_2(x))
+        return self.relu(self.branch_1(x) + self.branch_2(x))
 
 
 class DetailBranch(nn.Layer):

paddleseg/models/layers/wrap_functions.py

@@ -19,63 +19,63 @@
 """
 
 
-class add(nn.Layer):
+class Add(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, y, name=None):
         return paddle.add(x, y, name)
 
 
-class subtract(nn.Layer):
+class Subtract(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, y, name=None):
         return paddle.subtract(x, y, name)
 
 
-class multiply(nn.Layer):
+class Multiply(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, y, name=None):
         return paddle.multiply(x, y, name)
 
 
-class divide(nn.Layer):
+class Divide(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, y, name=None):
         return paddle.divide(x, y, name)
 
 
-class reshape(nn.Layer):
+class Reshape(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, shape, name=None):
         return paddle.reshape(x, shape, name)
 
 
-class transpose(nn.Layer):
+class Transpose(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, perm, name=None):
         return paddle.transpose(x, perm, name)
 
 
-class concat(nn.Layer):
+class Concat(nn.Layer):
     def __init__(self):
         super().__init__()
 
     def forward(self, x, axis=0, name=None):
         return paddle.concat(x, axis, name)
 
 
-class flatten(nn.Layer):
+class Flatten(nn.Layer):
     def __init__(self):
         super().__init__()