In Deep Learning Specialization, Course 2, Week 2, Programming Assignment: Optimization Methods, in ‘In [61]’ cell the ‘model’ function has been defined.
def model(X, Y, layers_dims, optimizer, learning_rate = 0.0007, mini_batch_size = 64, beta = 0.9,
beta1 = 0.9, beta2 = 0.999, epsilon = 1e-8, num_epochs = 5000, print_cost = True):
"""
3-layer neural network model which can be run in different optimizer modes.
Arguments:
X -- input data, of shape (2, number of examples)
Y -- true "label" vector (1 for blue dot / 0 for red dot), of shape (1, number of examples)
layers_dims -- python list, containing the size of each layer
learning_rate -- the learning rate, scalar.
mini_batch_size -- the size of a mini batch
beta -- Momentum hyperparameter
beta1 -- Exponential decay hyperparameter for the past gradients estimates
beta2 -- Exponential decay hyperparameter for the past squared gradients estimates
epsilon -- hyperparameter preventing division by zero in Adam updates
num_epochs -- number of epochs
print_cost -- True to print the cost every 1000 epochs
Returns:
parameters -- python dictionary containing your updated parameters
...
"""
In the function comments, there is a line describing each input except one input which is ‘optimizer’ input, is this comment line not written with purpose? if yes, please explain the purpose to me. If not, please report this to course support team in order to fix it.
I know it is just a minor thing but wanted to share it and there might be something to learn about here too.