| 84 | |
| 85 | |
| 86 | class Downsample3D(nn.Module): |
| 87 | def __init__( |
| 88 | self, channels, use_conv=False, out_channels=None, padding=1, name="conv" |
| 89 | ): |
| 90 | super().__init__() |
| 91 | self.channels = channels |
| 92 | self.out_channels = out_channels or channels |
| 93 | self.use_conv = use_conv |
| 94 | self.padding = padding |
| 95 | stride = 2 |
| 96 | self.name = name |
| 97 | |
| 98 | if use_conv: |
| 99 | self.conv = InflatedConv3d( |
| 100 | self.channels, self.out_channels, 3, stride=stride, padding=padding |
| 101 | ) |
| 102 | else: |
| 103 | raise NotImplementedError |
| 104 | |
| 105 | def forward(self, hidden_states): |
| 106 | assert hidden_states.shape[1] == self.channels |
| 107 | if self.use_conv and self.padding == 0: |
| 108 | raise NotImplementedError |
| 109 | |
| 110 | assert hidden_states.shape[1] == self.channels |
| 111 | hidden_states = self.conv(hidden_states) |
| 112 | |
| 113 | return hidden_states |
| 114 | |
| 115 | |
| 116 | class ResnetBlock3D(nn.Module): |