From 04be46e4bbbc5f1d5082fa99c3fe4fcd32e9e029 Mon Sep 17 00:00:00 2001 From: chenguowei01 Date: Tue, 22 Sep 2020 10:19:31 +0800 Subject: [PATCH] update layer_libs.py --- dygraph/paddleseg/models/common/layer_libs.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/dygraph/paddleseg/models/common/layer_libs.py b/dygraph/paddleseg/models/common/layer_libs.py index c0a4f16d..deb12a16 100644 --- a/dygraph/paddleseg/models/common/layer_libs.py +++ b/dygraph/paddleseg/models/common/layer_libs.py @@ -20,10 +20,10 @@ from paddle.nn import Conv2d from paddle.nn import SyncBatchNorm as BatchNorm -class ConvBNRelu(nn.Layer): +class ConvBNReLU(nn.Layer): def __init__(self, in_channels, out_channels, kernel_size, **kwargs): - super(ConvBNRelu, self).__init__() + super(ConvBNReLU, self).__init__() self._conv = Conv2d(in_channels, out_channels, kernel_size, **kwargs) @@ -40,9 +40,7 @@ class ConvBN(nn.Layer): def __init__(self, in_channels, out_channels, kernel_size, **kwargs): super(ConvBN, self).__init__() - self._conv = Conv2d(in_channels, out_channels, kernel_size, **kwargs) - self._batch_norm = BatchNorm(out_channels) def forward(self, x): @@ -69,16 +67,16 @@ class ConvReluPool(nn.Layer): return x -class DepthwiseConvBNRelu(nn.Layer): +class DepthwiseConvBNReLU(nn.Layer): def __init__(self, in_channels, out_channels, kernel_size, **kwargs): - super(DepthwiseConvBNRelu, self).__init__() + super(DepthwiseConvBNReLU, self).__init__() self.depthwise_conv = ConvBN( in_channels, out_channels=in_channels, kernel_size=kernel_size, groups=in_channels, **kwargs) - self.piontwise_conv = ConvBNRelu( + self.piontwise_conv = ConvBNReLU( in_channels, out_channels, kernel_size=1, groups=1) def forward(self, x): @@ -105,7 +103,7 @@ class AuxLayer(nn.Layer): dropout_prob=0.1): super(AuxLayer, self).__init__() - self.conv_bn_relu = ConvBNRelu( + self.conv_bn_relu = ConvBNReLU( in_channels=in_channels, out_channels=inter_channels, kernel_size=3, -- GitLab