Keras predict gives different error than evaluate, loss different from metrics
问题 I have the following problem: I have an autoencoder in Keras, and train it for a few epochs. The training overview shows a validation MAE of 0.0422 and an MSE of 0.0024. However, if I then call network.predict and manually calculate the validation errors, I get 0.035 and 0.0024. One would assume that my manual calculation of the MAE is simply incorrect, but the weird thing is that if I use an identity model (simply outputs what you input) and use that to evaluate the predicted values, the