(self, output_dim=[128], encoder_dim=[64, 96, 128])
| 92 | |
| 93 | class MultiBasicEncoder(nn.Module): |
| 94 | def __init__(self, output_dim=[128], encoder_dim=[64, 96, 128]): |
| 95 | super(MultiBasicEncoder, self).__init__() |
| 96 | |
| 97 | # output convolution for feature |
| 98 | self.conv2 = nn.Sequential( |
| 99 | ResidualBlock(encoder_dim[2], encoder_dim[2], stride=1), |
| 100 | nn.Conv2d(encoder_dim[2], encoder_dim[2] * 2, 3, padding=1)) |
| 101 | |
| 102 | # output convolution for context |
| 103 | output_list = [] |
| 104 | for dim in output_dim: |
| 105 | conv_out = nn.Sequential( |
| 106 | ResidualBlock(encoder_dim[2], encoder_dim[2], stride=1), |
| 107 | nn.Conv2d(encoder_dim[2], dim[2], 3, padding=1)) |
| 108 | output_list.append(conv_out) |
| 109 | |
| 110 | self.outputs08 = nn.ModuleList(output_list) |
| 111 | |
| 112 | def forward(self, x): |
| 113 | feat1, feat2 = self.conv2(x).split(dim=0, split_size=x.shape[0] // 2) |
nothing calls this directly
no test coverage detected