I'm currently working in python with tensorflow and would like to train my model with a gradient descent model and not a stochastic gradient descent model. The reason is that I want to train my model on all data points instead of a subset. Considering the different optimizers for tensorflow I found at: https://www.tensorflow.org/api_docs/python/tf/keras/optimizers I'm not sure if this is possible. Could someone explain me if there is way to do this?
Currently the code looks something like this:
model.compile(optimizer = 'adam', loss = 'mse')
Is there a gradient descent optimizer I could just fill in?
Thank you!