qq_45850131的博客

报错：RuntimeError: view size is not compatible with input tensor‘s size and stridedef attention_net(self, lstm_output, final_state): batch_size = lstm_output.size(0) hidden = final_state.view(batch_size, -1, 1) attn_weights

报错：UserWarning: Using a target size (torch.Size([15])) that is different to the input size (torch.Size([15, 1])).问题：训练模型时遇到以下报错解决方法：在forward(self, x)函数体中，在return x之前，加一句x = x.squeeze(-1)以达到降低一维的目的；def forward(self, x): H,(h,c) = self.lstm(x.

报错ValueError: too many values to unpack (expected 2)报错原因：定义的fit()函数的返回值有5个，而训练模型时只接收了两个函数的返回解决方法：将返回值都接收，即可成功运行；

ValueError: There are no more samples after a first-order seasonal differencing. See http://alkaline-ml.com/pmdarima/seasonal-differencing-issues.html for a more in-depth explanation and potential work-arounds.构建ARIMA模型时遇到以上报错Traceback (most recent call