I am trying to understand the tensorflow architectures and a way to see how the calculations were made to obtain a result in each epoch at history variable in model.fit() function:
history = model.fit(X_train, y_train, epochs=150, batch_size=16, verbose=0, validation_split=0.3, steps_per_epoch=10)
and at model.evaluate() function, about the final test accuracy and loss obtained:
loss, acc = model.evaluate(X_test, y_test, verbose=0)
I have tried to debug the functions behind model.fit and model.evaluate but I realized that there are lots of functions and it makes hard to understand how the calculations are made.
I want to know what should I do to visualize the calculations made in these two functions?