MockingBird
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替换模型训练遇到的问题
就是接着这个大佬的模型继续训练，因为我自己的模型太过于小了，无法收敛。但是一更换就报错 截图在下面 然后我再复制粘贴一下防止我没传上来图片
E:\数据集制作\MockingBird-main\synthesizer\synthesizer_dataset.py:84: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ..\torch\csrc\utils\tensor_new.cpp:201.)
embeds = torch.tensor(embeds)
C:\Users\11351\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\nn\functional.py:1795: UserWarning: nn.functional.tanh is deprecated. Use torch.tanh instead.
warnings.warn("nn.functional.tanh is deprecated. Use torch.tanh instead.")
Traceback (most recent call last):
File "E:\数据集制作\MockingBird-main\synthesizer_train.py", line 37, in 
社区的模型都试过了，除了谷歌DIrve的下不了之外。其他的都试过了，也是报错。 https://pan.baidu.com/s/1fMh9IlgKJlL2PIiRTYDUvw 百度盘链接 提取码：om7f 这个大佬的是这个代码 RuntimeError: Error(s) in loading state_dict for Tacotron: size mismatch for encoder.embedding.weight: copying a param with shape torch.Size([70, 512]) from checkpoint, the shape in current model is torch.Size([75, 512]). size mismatch for encoder_proj.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([128, 1024]). size mismatch for decoder.attn_rnn.weight_ih: copying a param with shape torch.Size([384, 768]) from checkpoint, the shape in current model is torch.Size([384, 1280]). size mismatch for decoder.rnn_input.weight: copying a param with shape torch.Size([1024, 640]) from checkpoint, the shape in current model is torch.Size([1024, 1152]). size mismatch for decoder.stop_proj.weight: copying a param with shape torch.Size([1, 1536]) from checkpoint, the shape in current model is torch.Size([1, 2048]).
https://pan.baidu.com/s/1PI-hM3sn5wbeChRryX-RCQ 提取码：2021这个的是下面的 就是我的数据量要匹配这个模型才可以么 RuntimeError: Error(s) in loading state_dict for Tacotron: size mismatch for encoder.embedding.weight: copying a param with shape torch.Size([70, 512]) from checkpoint, the shape in current model is torch.Size([75, 512]). size mismatch for encoder_proj.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([128, 1024]). size mismatch for decoder.attn_rnn.weight_ih: copying a param with shape torch.Size([384, 768]) from checkpoint, the shape in current model is torch.Size([384, 1280]). size mismatch for decoder.rnn_input.weight: copying a param with shape torch.Size([1024, 640]) from checkpoint, the shape in current model is torch.Size([1024, 1152]). size mismatch for decoder.stop_proj.weight: copying a param with shape torch.Size([1, 1536]) from checkpoint, the shape in current model is torch.Size([1, 2048]).
不是数据量问题，而是你的模型和代码版本不一致，你下载前要看模型是哪个代码版本，要切换过去（版本切换请学git）
我用的tag 0.01 的版本预处理然后换了模型（用的是ceshi）发现继续训练的时候会出现valueerror， 具体为：
Loading weights at synthesizer\saved_models\chenlin\chenlin.pt
Traceback (most recent call last):
File "D:\Downloads\MockingBird-0.0.1\synthesizer_train.py", line 37, in
