Web1 de jul. de 2024 · On training, the LSTM layer returns nan for its hidden state after one iteration. There is a similar issue here: Getting nan for gradients with LSTMCell We are doing a customized LSTM using LSTMCell, on a binary classification, loss is BCEwithlogits. We traced the problem back to loss.backward (). Web17 de set. de 2024 · 更新2 我已将TensorFlow和Keras升级到版本1.12.0和2.2.4。没有效果。 我也尝试按照@Oluwafemi Sule的建议在第一个LSTM层添加一个损失，它看起来像是朝着正确的方向迈出了一步，现在第一个时代的损失不是纳米，但是，我仍然得到同样的错误.....可能是因为其他的nan值，比如val_loss / val_f1。

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Web15 de mai. de 2016 · I had the same problem with my RNN with keras LSTM layers, so I tried each solution from above. I had already scaled my data (with … WebI got Nans for all loss functions. Here is what I would do: either drop the scaler.fit (y) and only do the yscale=scaler.transform (y) OR have two different scalers for x and y. Especially if your y values are in a very different number range from your x values. Then the normalization is "off" for x. Share Improve this answer Follow how many units is one college class

关于python：Keras – Nan在摘要直方图LSTM中 码农家园

WebThe extra layer made the gradients too unstable, and that lead to the loss function quickly devolving to NaN. The best way to fix this is to use Xavier initialization. Otherwise, the variance of the initial values will tend to be too high, causing instability. Also, decreasing the learning rate may help. Web一个基于Python的示例代码，以实现一个用于进行队列到队列的预测的LSTM模型。请注意，这个代码仅供参考，您可能需要根据您的具体数据和需求进行一些调整和优化 ... 我们 … WebLSTM Time Series problem, Loss became NaN. Why? Hi everyone, i'm working for predictive maintenance with a long time series of data, around 75000 time steps with 18 … how many units is one beer