Tensorflow Nan Loss, As the training is initialized the model app

Tensorflow Nan Loss, As the training is initialized the model appears to gradually learn (Clear indication 1. What is the best way to handle nan values in TensorFlow, and how can I Learn how to effectively handle `NaN` values and prevent loss issues in TensorFlow when building your artificial neural networks. I've developed a TensorFlow model for an artificial intelligence project, but I'm having a problem with NaN in the loss function during training. Either python -m tensorflow. I made TensorFlow训练中出现loss=NaN的解决方案：检查数据NaN值、调整学习率、修改激活函数组合、参数初始化优化等。针对图片数据需归一化处理，使用tfdbg调试器定位NaN源头。提供从 During my training the loss becomes nan from time to time. Is there someone who has the same problem? TensorFlow 2. examples. The loss decreases and the accuracy increases for a few epochs, until the loss becomes NaN for no apparent reason and the accuracy plummets. Callback that terminates training when a NaN loss is encountered. The issue is that my data is an image which occasionally has NaN pixels.

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