@ -42,7 +42,8 @@ class AIlib:
print(dCost, dProp)
return dCost / dProp
def gradient( inp:np.array, obj, theta:float, maxLayer:int, layerIndex: int=0, grads: list, obj1=None, obj2=None ): # Calculate the gradient for that prop
def gradient( inp:np.array, obj, theta:float, maxLayer:int, layerIndex: int=0, grads=None, obj1=None, obj2=None ): # Calculate the gradient for that prop
# Check if grads exists, if not create the buffer
if( not grads ):
grads = [None] * maxLayer