(self, in_features, out_features, kernel_size=3, padding=1, groups=1)
| 105 | """ |
| 106 | |
| 107 | def __init__(self, in_features, out_features, kernel_size=3, padding=1, groups=1): |
| 108 | super(UpBlock3d, self).__init__() |
| 109 | |
| 110 | self.conv = nn.Conv3d(in_channels=in_features, out_channels=out_features, kernel_size=kernel_size, |
| 111 | padding=padding, groups=groups) |
| 112 | self.norm = nn.BatchNorm3d(out_features, affine=True) |
| 113 | |
| 114 | def forward(self, x): |
| 115 | out = F.interpolate(x, scale_factor=(1, 2, 2)) |