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fix: Fix the dimension bug of BasicBlock #8

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fix: Fix the dimension bug of BasicBlock #8

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12 changes: 6 additions & 6 deletions resnext.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,22 +10,22 @@
__all__ = ['ResNeXt', 'resnext18', 'resnext34', 'resnext50', 'resnext101',
'resnext152']

def conv3x3(in_planes, out_planes, stride=1):
def conv3x3(in_planes, out_planes, stride=1, groups=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
padding=1, groups=groups, bias=False)


class BasicBlock(nn.Module):
expansion = 1

def __init__(self, inplanes, planes, stride=1, downsample=None, num_group=32):
super(BasicBlock, self).__init__()
self.conv1 = conv3x3(inplanes, planes*2, stride)
self.bn1 = nn.BatchNorm2d(planes*2)
self.conv1 = conv3x3(inplanes, planes, stride)
self.bn1 = nn.BatchNorm2d(planes)
self.relu = nn.ReLU(inplace=True)
self.conv2 = conv3x3(planes*2, planes*2, groups=num_group)
self.bn2 = nn.BatchNorm2d(planes*2)
self.conv2 = conv3x3(planes, planes, groups=num_group)
self.bn2 = nn.BatchNorm2d(planes)
self.downsample = downsample
self.stride = stride

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