Why am I getting same output values for every single data in my ann model for multi-class classification?

The task is to classify a multi-spectral image(4 bands) into 3 classes. and i had to do pixel-based classification. So, the structure of the code that i pasted here is the exact replica of my original code except for the data which is a random array here.
I was stuck with these similar outputs and same predicted class label. So, i tried doing it on a random array first to correct the errors.
If i get same output class labels on all the training data too, what changes should be made in the model?
Could u plz suggest what factors should be modified to get different results. That’ll be really helpful.