Fizz Buzz in tensorflow

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
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"]=‘3‘
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#这位是1吗
            num = num>>1#右移一位
            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))#100个neuron(hidden layer)
model.add(Activation(‘relu‘))
model.add(Dense(output_dim=4))#4种情况
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])