未验证 提交 88c25c7f 编写于 作者: W wuzewu 提交者: GitHub

Merge pull request #392 from wuyefeilin/dygraph

......@@ -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)
......@@ -36,10 +36,10 @@ class ConvBnRelu(nn.Layer):
return x
class ConvBn(nn.Layer):
class ConvBN(nn.Layer):
def __init__(self, in_channels, out_channels, kernel_size, **kwargs):
super(ConvBn, self).__init__()
super(ConvBN, self).__init__()
self.conv = Conv2d(in_channels, out_channels, kernel_size, **kwargs)
......@@ -69,16 +69,16 @@ 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__()
self.depthwise_conv = ConvBn(
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 +105,7 @@ 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,
......@@ -123,4 +123,3 @@ class AuxLayer(nn.Layer):
x = F.dropout(x, p=self.dropout_prob)
x = self.conv(x)
return x
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