C:\Users\Administrator\AppData\Local\Programs\Python\Python37\python.exe D:/pycharm/system/py/2.py Traceback (most recent call last): File "D:/pycharm/system/py/2.py", line 66, in <module> model = TransformerModel(input_size, output_size, nhead, num_layers, hidden_size, dropout) File "D:/pycharm/system/py/2.py", line 24, in __init__ self.transformer_encoder = nn.TransformerEncoder(nn.TransformerEncoderLayer(input_size, nhead, hidden_size, dropout), num_layers) File "C:\Users\Administrator\AppData\Local\Programs\Python\Python37\lib\site-packages\torch\nn\modules\transformer.py", line 302, in __init__ **factory_kwargs) File "C:\Users\Administrator\AppData\Local\Programs\Python\Python37\lib\site-packages\torch\nn\modules\activation.py", line 918, in __init__ assert self.head_dim * num_heads == self.embed_dim, "embed_dim must be divisible by num_heads" AssertionError: embed_dim must be divisible by num_heads

这个错误提示是因为在使用 nn.TransformerEncoderLayer 创建 TransformerEncoder 时，输入参数 embed_dim 必须能够被 num_heads 整除。embed_dim 是 TransformerEncoderLayer 的输入和输出维度，num_heads 是多头自注意力机制中头的数量。你可以通过调整 input_size 和 nhead 参数，使得 embed_dim 能够被 num_heads 整除。比如，你可以将 input_size 设置为 256，nhead 设置为 8。