| 9 | |
| 10 | |
| 11 | def convert_bn(blobs, state_dict, caffe_name, torch_name, converted_names): |
| 12 | # detectron replace bn with affine channel layer |
| 13 | state_dict[torch_name + '.bias'] = torch.from_numpy(blobs[caffe_name + |
| 14 | '_b']) |
| 15 | state_dict[torch_name + '.weight'] = torch.from_numpy(blobs[caffe_name + |
| 16 | '_s']) |
| 17 | bn_size = state_dict[torch_name + '.weight'].size() |
| 18 | state_dict[torch_name + '.running_mean'] = torch.zeros(bn_size) |
| 19 | state_dict[torch_name + '.running_var'] = torch.ones(bn_size) |
| 20 | converted_names.add(caffe_name + '_b') |
| 21 | converted_names.add(caffe_name + '_s') |
| 22 | |
| 23 | |
| 24 | def convert_conv_fc(blobs, state_dict, caffe_name, torch_name, |