import numpy as np
import utils
# Forward Neural Network (FNN)
class FNN:
# layers = 3 and shape = [input dim, xx, class num]
def __init__(self, shape, activation='sigmoid') -> None:
self._l = len(shape) - 1 # layer number
self._w = [] # weight
self._b = [] # bias
self._z = [i for i in range(self._l)] # wx+b
self._a = [i for i in range(self._l)] # activation(wx+b)
self._x = None # input feature
self._n = None # batch size
神经网络
import numpy as np import utils # Forward Neural Network (FNN) class FNN: # layers = 3 and shape = [input dim, xx, class num] def __init__(self, shape,