Moving averaging of Loss during Training in Keras

I am using Keras with TensorFlow to implement a deep neural network. When I plot the loss and number of iterations, there is a significant jump in loss after each epoch. In reality, the loss of each mini-batch should vary from each other, but Keras calculates the moving average of the loss over the mini-batches, that’s why we obtain a smooth curve instead of an arbitrary one. The array of the moving average is reset after each epoch because of which we can observe a jump in the loss.

Make a custom loss function in keras

Hi I have been trying to make a custom loss function in keras for dice_error_coefficient. It has its implementations in tensorboard and I tried using the same function in keras with tensorflow but it keeps returning a NoneType when I used model.train_on_batch or where as it gives proper values when used in metrics in the model. Can please someone help me out with what should i do? I have tried following libraries like Keras-FCN by ahundt where he has used custom loss functions but none of it seems to work. The target and output in the code are y_true and y_pred respectively as used in the file in keras.

TensorFlow Only running on 1/32 of the Training data provided

I’ve implemented a neural network using tensor flow and it appears to be only running on 1/32 data points. I’ve then tried to following simple example to see if it was me: Even when using identical (copied and pasted) code I still get 1/32 of the training data being processed e.g. Epoch 3/3 1875/1875 … Read more

How to export Keras .h5 to tensorflow .pb?

I have fine-tuned inception model with a new dataset and saved it as “.h5” model in Keras. now my goal is to run my model on android Tensorflow which accepts “.pb” extension only. question is that is there any library in Keras or tensorflow to do this conversion? I have seen this post so far : but can’t figure out yet.