diff options
| -rw-r--r-- | models/model.py | 4 | ||||
| -rw-r--r-- | models/rgb_part_net.py | 2 |
2 files changed, 4 insertions, 2 deletions
diff --git a/models/model.py b/models/model.py index 7dba949..4354b35 100644 --- a/models/model.py +++ b/models/model.py @@ -81,12 +81,14 @@ class Model: @staticmethod def init_weights(m): if isinstance(m, nn.modules.conv._ConvNd): - nn.init.xavier_uniform_(m.weight) + nn.init.normal_(m.weight, 0.0, 0.01) elif isinstance(m, nn.modules.batchnorm._NormBase): nn.init.normal_(m.weight, 1.0, 0.01) nn.init.zeros_(m.bias) elif isinstance(m, nn.Linear): nn.init.xavier_uniform_(m.weight) + elif isinstance(m, RGBPartNet): + nn.init.xavier_uniform_(m.fc_mat) def _parse_dataset_config( self, diff --git a/models/rgb_part_net.py b/models/rgb_part_net.py index ac76dbf..5012765 100644 --- a/models/rgb_part_net.py +++ b/models/rgb_part_net.py @@ -41,7 +41,7 @@ class RGBPartNet(nn.Module): ) total_parts = sum(hpm_scales) + tfa_num_parts empty_fc = torch.empty(total_parts, out_channels, embedding_dims) - self.fc_mat = nn.init.xavier_uniform_(nn.Parameter(empty_fc)) + self.fc_mat = nn.Parameter(empty_fc) def fc(self, x): return torch.matmul(x, self.fc_mat) |