import tensorflow
from sklearn.datasets import load_iris
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

iris = load_iris()
X = iris.data
Y = iris.target
y= tensorflow.keras.utils.to_categorical(Y)

model = Sequential()
model.add(Dense(8, input_dim=4, activation = 'relu'))
model.add(Dense(8,activation='relu'))
model.add(Dense(3,activation='softmax'))

model.compile(optimizer='adam', loss='categorical_crossentropy',metrics=['accuracy'])
model.fit(X,y, batch_size=5, epochs = 200)
model.save('iris.h5')
print(model.summary)