Training the network from scratch: Training, Validation Loss & Metric

[iamsharmatul]

Dear @zhangjun001,

I am using your network for my research. I want to learn about the network therefore I have some questions.

1. Loss:

I am curious to know how did you compute validation loss while training. As I see in the code that the training loop is based on steps(iteration) and not on epochs. so did you compute validation loss for each step ? if yes which of the following example did you use.

Example:

1. after each step validation_data_gen will load all the validation samples and the mean loss will be logged for all 4 losses.
2. after each step one pair from validation_data_gen will be used to calculate the validation loss for all 4 losses.

If there is some other strategy could you please share?

2. Training:

The network is trained on all possible pairs of combinations of the dataset. Is this the best practice? or we can use epochs and steps_per_epoch setting where data generator returns any 2 random images.

3. Metric:
   Should I only use metrics during testing or can I use some custom metrics during training as well just to log the performance of the network step by step?

Thanks in advance