change KaimingNormal to KaimingUniform
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@ -58,7 +58,7 @@ class Head(nn.Layer):
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stride=2,
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weight_attr=ParamAttr(
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name=name_list[2] + '.w_0',
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initializer=paddle.nn.initializer.KaimingNormal()),
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initializer=paddle.nn.initializer.KaimingUniform()),
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bias_attr=get_bias_attr(in_channels // 4, name_list[-1] + "conv2"))
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self.conv_bn2 = nn.BatchNorm(
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num_channels=in_channels // 4,
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@ -78,7 +78,7 @@ class Head(nn.Layer):
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stride=2,
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weight_attr=ParamAttr(
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name=name_list[4] + '.w_0',
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initializer=paddle.nn.initializer.KaimingNormal()),
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initializer=paddle.nn.initializer.KaimingUniform()),
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bias_attr=get_bias_attr(in_channels // 4, name_list[-1] + "conv3"),
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)
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@ -26,7 +26,7 @@ class DBFPN(nn.Layer):
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def __init__(self, in_channels, out_channels, **kwargs):
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super(DBFPN, self).__init__()
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self.out_channels = out_channels
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weight_attr = paddle.nn.initializer.KaimingNormal()
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weight_attr = paddle.nn.initializer.KaimingUniform()
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self.in2_conv = nn.Conv2D(
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in_channels=in_channels[0],
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