import tensorflow as tf
from tensorflow import keras
import numpy as np

tfe = tf.contrib.eager
tf.enable_eager_execution()
i4 = np.eye(4)
inds = np.random.randint(0,4,size=2000)
data = i4[inds]
model = keras.Sequential([keras.layers.Dense(4, kernel_regularizer=
                         keras.regularizers.l2(.001), kernel_initializer='zeros')])
model.compile(optimizer=tf.train.AdamOptimizer(.001), loss= 'mse',  metrics = ['accuracy'])
model.fit(data,inds, epochs=50)

model.fit(data, data, epochs =50)