| 115 | |
| 116 | |
| 117 | class Fuser(nn.Module): |
| 118 | |
| 119 | def __init__(self, layer, num_layers, dim=None, input_projection=False): |
| 120 | super().__init__() |
| 121 | self.proj = nn.Identity() |
| 122 | # NOTE: avoid using copy.deepcopy with zero3 or ZeroGPUs |
| 123 | self.layers = nn.ModuleList([CXBlock(**layer) for _ in range(num_layers)]) |
| 124 | # self.layers = get_clones(layer, num_layers) |
| 125 | |
| 126 | if input_projection: |
| 127 | assert dim is not None |
| 128 | self.proj = nn.Conv2d(dim, dim, kernel_size=1) |
| 129 | |
| 130 | def forward(self, x): |
| 131 | # normally x: (N, C, H, W) |
| 132 | x = self.proj(x) |
| 133 | for layer in self.layers: |
| 134 | x = layer(x) |
| 135 | return x |
| 136 | |
| 137 | |
| 138 | class MemoryEncoder(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected