change KaimingNormal to KaimingUniform

ppocr/modeling/heads/det_db_head.py

@@ -58,7 +58,7 @@ class Head(nn.Layer):
             stride=2,
             weight_attr=ParamAttr(
                 name=name_list[2] + '.w_0',
-                initializer=paddle.nn.initializer.KaimingNormal()),
+                initializer=paddle.nn.initializer.KaimingUniform()),
             bias_attr=get_bias_attr(in_channels // 4, name_list[-1] + "conv2"))
         self.conv_bn2 = nn.BatchNorm(
             num_channels=in_channels // 4,
@@ -78,7 +78,7 @@ class Head(nn.Layer):
             stride=2,
             weight_attr=ParamAttr(
                 name=name_list[4] + '.w_0',
-                initializer=paddle.nn.initializer.KaimingNormal()),
+                initializer=paddle.nn.initializer.KaimingUniform()),
             bias_attr=get_bias_attr(in_channels // 4, name_list[-1] + "conv3"),
         )
 

ppocr/modeling/necks/db_fpn.py

@@ -26,7 +26,7 @@ class DBFPN(nn.Layer):
     def __init__(self, in_channels, out_channels, **kwargs):
         super(DBFPN, self).__init__()
         self.out_channels = out_channels
-        weight_attr = paddle.nn.initializer.KaimingNormal()
+        weight_attr = paddle.nn.initializer.KaimingUniform()
 
         self.in2_conv = nn.Conv2D(
             in_channels=in_channels[0],