def __init__(self, num_classes):
super().__init__(num_classes)
self.conv1 = nn.Conv2d(1, 32, kernel_size=5)
self.conv1_drop = mc_dropout.MCDropout2d()
self.conv2 = nn.Conv2d(32, 64, kernel_size=5)
self.conv2_drop = mc_dropout.MCDropout2d()
self.fc1 = nn.Linear(1024, 128)
self.fc1_drop = mc_dropout.MCDropout()
self.fc2 = nn.Linear(128, num_classes)
def __init__(self, num_classes):
super().__init__(num_classes)
self.num_classes = num_classes
self.conv1 = nn.Conv2d(1, 32, kernel_size=3)
self.conv1_drop = mc_dropout.MCDropout2d()
self.conv2 = nn.Conv2d(32, 64, kernel_size=3)
self.conv2_drop = mc_dropout.MCDropout2d()
self.conv3 = nn.Conv2d(64, 128, kernel_size=3)
self.conv3_drop = mc_dropout.MCDropout2d()
self.fc1 = nn.Linear(128 * 4 * 4, 512)
self.fc1_drop = mc_dropout.MCDropout()
self.fc2 = nn.Linear(512, num_classes)
def __init__(self, num_classes):
super().__init__(num_classes)
self.num_classes = num_classes
self.conv1 = nn.Conv2d(3, 32, kernel_size=3, padding=1)
self.conv1_drop = mc_dropout.MCDropout2d()
self.bn1 = nn.BatchNorm2d(32)
self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
self.conv2_drop = mc_dropout.MCDropout2d()
self.bn2 = nn.BatchNorm2d(64)
self.conv3 = nn.Conv2d(64, 128, kernel_size=3, padding=1)
self.conv3_drop = mc_dropout.MCDropout2d()
self.bn3 = nn.BatchNorm2d(128)
self.conv4 = nn.Conv2d(128, 128, kernel_size=3, padding=1)
self.conv4_drop = mc_dropout.MCDropout2d()
self.bn4 = nn.BatchNorm2d(128)
self.conv5 = nn.Conv2d(128, 256, kernel_size=3, padding=1)
self.conv5_drop = mc_dropout.MCDropout2d()
self.bn5 = nn.BatchNorm2d(256)
self.conv6 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
self.conv6_drop = mc_dropout.MCDropout2d()
self.bn6 = nn.BatchNorm2d(256)
self.conv7 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
self.conv7_drop = mc_dropout.MCDropout2d()
self.bn7 = nn.BatchNorm2d(256)
self.conv8 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
self.conv8_drop = mc_dropout.MCDropout2d()
self.bn8 = nn.BatchNorm2d(256)
self.avgpool = nn.AdaptiveAvgPool2d((1, 1))
#self.avgpool = nn.AvgPool2d(kernel_size=1, stride=1)
self.fc1 = nn.Linear(256, 512)
self.fc1_drop = mc_dropout.MCDropout()
self.fc2 = nn.Linear(512, 512)
self.fc2_drop = mc_dropout.MCDropout()
self.fc3 = nn.Linear(512, num_classes)