替换模型之后训练时报错

**Summary[问题简述（一句话）]**
A clear and concise description of what the issue is.
[替换模型之后训练时报错](url)
**Env & To Reproduce[复现与环境]**
描述你用的环境、代码版本、模型
python3.9 mockingbird0.0.1 75k模型
**Screenshots[截图（如有）]**
Arguments:
run_id: mandarin
syn_dir: F:/AI/mockingbird3/SV2TTS/synthesizer
models_dir: synthesizer/saved_models/
save_every: 1000
backup_every: 25000
log_every: 200
force_restart: False
hparams:

Checkpoint path: synthesizer\saved_models\mandarin\mandarin.pt
Loading training data from: F:\AI\mockingbird3\SV2TTS\synthesizer\train.txt
Using model: Tacotron
Using device: cuda

Initialising Tacotron Model...

Trainable Parameters: 30.875M

Loading weights at synthesizer\saved_models\mandarin\mandarin.pt
Traceback (most recent call last):
File "F:\AI\mockingbird3\synthesizer_train.py", line 37, in
train(**vars(args))
File "F:\AI\mockingbird3\synthesizer\train.py", line 114, in train
model.load(weights_fpath, device, optimizer)
File "F:\AI\mockingbird3\synthesizer\models\tacotron.py", line 550, in load
optimizer.load_state_dict(checkpoint["optimizer_state"])
File "F:\back\envs\mockingbrid\lib\site-packages\torch\optim\optimizer.py", line 390, in load_state_dict
raise ValueError("loaded state dict contains a parameter group "
ValueError: loaded state dict contains a parameter group that doesn't match the size of optimizer's group

Start with synthesizer/models/tacotron.py, where load calls optimizer.load_state_dict, and trace how synthesizer/train.py invokes it. Reproduce the failure using the shown Python 3.9 environment and mandarin.pt checkpoint, then verify that training can resume with the replacement model without the parameter-group error.

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