求帮助改进

[CX520-afx]

Loading checkpoint from expr/checkpoints/celeba_hq\100000_nets_ema.ckpt...
Traceback (most recent call last):
File "D:\QQQ\stargan-v2-master\main.py", line 182, in
main(args)
File "D:\QQQ\stargan-v2-master\main.py", line 73, in main
solver.sample(loaders)
File "D:\pycharm\python_study\pythonProject1\Graduate.venv\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "D:\QQQ\stargan-v2-master\core\solver.py", line 178, in sample
self._load_checkpoint(args.resume_iter)
File "D:\QQQ\stargan-v2-master\core\solver.py", line 73, in _load_checkpoint
ckptio.load(step)
File "D:\QQQ\stargan-v2-master\core\checkpoint.py", line 48, in load
module.module.load_state_dict(module_dict[name])
File "D:\pycharm\python_study\pythonProject1\Graduate.venv\Lib\site-packages\torch\nn\modules\module.py", line 2581, in load_state_dict
raise RuntimeError(
RuntimeError: Error(s) in loading state_dict for Generator:
Missing key(s) in state_dict: "decode.3.conv1x1.weight".
Unexpected key(s) in state_dict: "encode.6.conv1.weight", "encode.6.conv1.bias", "encode.6.conv2.weight", "encode.6.conv2.bias", "encode.6.norm1.weight", "encode.6.norm1.bias", "encode.6.norm2.weight", "encode.6.norm2.bias", "decode.6.conv1.weight", "decode.6.conv1.bias", "decode.6.conv2.weight", "decode.6.conv2.bias", "decode.6.norm1.fc.weight", "decode.6.norm1.fc.bias", "decode.6.norm2.fc.weight", "decode.6.norm2.fc.bias", "decode.6.conv1x1.weight".
size mismatch for decode.3.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]).
size mismatch for decode.3.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decode.3.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decode.3.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decode.3.norm2.fc.weight: copying a param with shape torch.Size([1024, 64]) from checkpoint, the shape in current model is torch.Size([512, 64]).
size mismatch for decode.3.norm2.fc.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for decode.4.conv1.weight: copying a param with shape torch.Size([256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]).
size mismatch for decode.4.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decode.4.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decode.4.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decode.4.norm1.fc.weight: copying a param with shape torch.Size([1024, 64]) from checkpoint, the shape in current model is torch.Size([512, 64]).
size mismatch for decode.4.norm1.fc.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for decode.4.norm2.fc.weight: copying a param with shape torch.Size([512, 64]) from checkpoint, the shape in current model is torch.Size([256, 64]).
size mismatch for decode.4.norm2.fc.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decode.4.conv1x1.weight: copying a param with shape torch.Size([256, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]).
size mismatch for decode.5.conv1.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]).
size mismatch for decode.5.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for decode.5.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for decode.5.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for decode.5.norm1.fc.weight: copying a param with shape torch.Size([512, 64]) from checkpoint, the shape in current model is torch.Size([256, 64]).
size mismatch for decode.5.norm1.fc.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decode.5.norm2.fc.weight: copying a param with shape torch.Size([256, 64]) from checkpoint, the shape in current model is torch.Size([128, 64]).
size mismatch for decode.5.norm2.fc.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decode.5.conv1x1.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]).