记录李宏毅机器学习的FiZZ BUZZ程序代码问题——TypeError: __init__() missing 1 required positional argument: ‘units‘

记录李宏毅机器学习的FiZZ BUZZ程序代码问题——TypeError: init() missing 1 required positional argument: ‘units’

李宏毅老师给的参考代码如下：

from keras.layers.normalization import BatchNormalization
from keras.models import Sequential
from keras.layers.core import Dense,Dropout,Activation
from keras.optimizers import SGD,Adam
import numpy as np

def fizzbuzz(start,end):
    x_train,y_train=[],[]
    for i in range(start,end+1):
        num = i
        tmp=[0]*10
        j=0
        while num :
            tmp[j] = num & 1
            num = num>>1
            j+=1        
        x_train.append(tmp)
        if i % 3 == 0 and i % 5 ==0:
            y_train.append([0,0,0,1])
        elif i % 3 == 0:
            y_train.append([0,1,0,0])
        elif i % 5 == 0:
            y_train.append([0,0,1,0])
        else :
            y_train.append([1,0,0,0])
    return np.array(x_train),np.array(y_train)

x_train,y_train = fizzbuzz(101,1000) #打标记函数
x_test,y_test = fizzbuzz(1,100)

model = Sequential()
model.add(Dense(input_dim=10,output_dim=100))
model.add(Activation('relu'))
model.add(Dense(output_dim=4))
model.add(Activation('softmax'))

model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])

model.fit(x_train,y_train,batch_size=20,nb_epoch=100)

result = model.evaluate(x_test,y_test,batch_size=1000)

print('Acc：',result[1])`

运行结果出错：结果如下：

Traceback (most recent call last):
  File "C:\Users\19025\Desktop\sublime\练习\sjwl.py", line 84, in <module>
    model.add(Dense(input_dim=10,output_dim=100))
TypeError: __init__() missing 1 required positional argument: 'units'

错误是因为：
model.add(Dense(input_dim=10,output_dim=100))
中间缺少units这个量，其实是因为output_dim在新版本中就是units，相应位置程序修改为：

model.add(Dense(input_dim=10,units=100))

model.add(Dense(units=4))

依旧报错，报错信息如下：

Traceback (most recent call last):
  File "C:\Users\19025\Desktop\sublime\练习\sjwl.py", line 91, in <module>
    model.fit(x_train,y_train,batch_size=20,nb_epoch=100)
  File "D:\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py", line 108, in _method_wrapper
    return method(self, *args, **kwargs)
TypeError: fit() got an unexpected keyword argument 'nb_epoch'

这是因为新版本nb_epoch改为epochs,
修改相应代码：

model.fit(x_train,y_train,batch_size=20,epochs=100)

运行，成功！
完整程序如下：

from keras.layers.normalization import BatchNormalization
from keras.models import Sequential
from keras.layers.core import Dense,Dropout,Activation
from keras.optimizers import SGD,Adam
import numpy as np

def fizzbuzz(start,end):
    x_train,y_train=[],[]
    for i in range(start,end+1):
        num = i
        tmp=[0]*10
        j=0
        while num :
            tmp[j] = num & 1
            num = num>>1
            j+=1        
        x_train.append(tmp)
        if i % 3 == 0 and i % 5 ==0:
            y_train.append([0,0,0,1])
        elif i % 3 == 0:
            y_train.append([0,1,0,0])
        elif i % 5 == 0:
            y_train.append([0,0,1,0])
        else :
            y_train.append([1,0,0,0])
    return np.array(x_train),np.array(y_train)

x_train,y_train = fizzbuzz(101,1000) #打标记函数
x_test,y_test = fizzbuzz(1,100)

model = Sequential()
model.add(Dense(input_dim=10,units=100))
model.add(Activation('relu'))
model.add(Dense(units=4))
model.add(Activation('softmax'))

model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])

model.fit(x_train,y_train,batch_size=20,epochs=100)

result = model.evaluate(x_test,y_test,batch_size=1000)

print('Acc：',result[1])