Ive been working on some code recently for a project in python and im confused by the output im getting from this code
def sigmoid(input_matrix):
rows = input_matrix.shape[0]
columns = input_matrix.shape[1]
for i in range(0,rows):
for j in range(0,columns):
input_matrix[i,j] = (1 / (1 + math.exp(-(input_matrix[i,j]))))
return input_matrix
def feed_forward(W_L_1 , A_L_0 , B_L_1):
weighted_sum = np.add(np.dot(W_L_1,A_L_0), B_L_1)
activation = sigmoid(weighted_sum)
return [weighted_sum,activation]
a = np.zeros((1,1))
b = feed_forward(a,a,a)
print(b[0])
print(b[1])
when I print both b[0] and b[1] give values of .5 even though b[0] should equal 0. Also in addition to this when I place the '''weighted_sum = np.add(np.dot(W_L_1,A_L_0), B_L_1)''' again after the 'actvation' line it provides the correct result. Its as if the 'activation' line has changed the value of the weighted sum value.
Was wondering if anyone could spread some light on this I can work around this but am interested as to why this is happening. Thanks!!
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