Low accuracy using Multi Layer perceptron network on CIFAR10 dataset?
CIFAR10 has 10 class label. So by random guessing, you should achieve an accuracy of 10%. And this is what you are getting. This means your algorithm is not learning at all. The most common problem causes this is your learning rate. Reduce your learning rate by replacing your line,

model.fit(X_tr,Yt,validation_data=(X_ts,Yts),epochs=10,batch_size=200,verbose=2)


with 

optimizer = keras.optimizers.Adam(lr=1e-4)
model.compile(loss='squared_hinge',optimizer=optimizer,metrics=['accuracy'])


I just did a test run, it is learning slowly.