Forward Propagation

nn-step2.py

def linear_forward(z, w, b):
	Z = z.dot(w)
	Z = Z + b
	stash = (z,w,b)
	
	return Z,stash

def activation_function(activation, z):
	if activation == "relu":
		a = np.maximum(0,z)
		stash = z
	elif activation == "sigmoid":
		a = 1/(1+np.exp(-1*z))
		stash = z
	return a,stash
	
def forward_pass(X, params):
	stashes = []
	A = X
	L = len(params) // 2
	for l in range(1,L):
		Z_prev = A
		Z,linear_stash = linear_forward(Z_prev,params['W'+str(l)],params['b'+str(l)])
		A,activation_stash = activation_function("relu",Z)
		stash = (linear_stash,activation_stash)
		stashes.append(stash)

	Z_,linear_stash = linear_forward(A,params['W'+str(L)],params['b'+str(L)])
	A_,activation_stash = activation_function("sigmoid",Z_)
	stash = (linear_stash,activation_stash)
	stashes.append(stash)
	return A_,stashes