#1. 데이터
import numpy as np
x = np.array([1,2,3,4,5,6,7,8,9,10])
y = np.array([1,2,3,4,5,6,7,8,9,10])
# x2 = np.array([4,5,6])


#2. 모델 구성
from keras.models import Sequential
from keras.layers import Dense
model = Sequential() #순차적으로, 모델링

model.add(Dense(5, input_dim = 1, activation = 'relu')) #input_dim: 1개 밀어넣음
model.add(Dense(3))
model.add(Dense(4))
model.add(Dense(1))

model.summary()


# #3. 훈련
# model.compile(loss = 'mse', optimizer = 'adam', metrics=['accuracy'] )
# # model.fit(x, y, epochs=610, batch_size=3)
# model.fit(x, y, epochs=100)


# #4. 평가 예측
# loss, acc = model.evaluate(x, y, batch_size=32)
# print("acc : ", acc)

# y_predict = model.predict(x2) #x는 훈련시킨 값
# print(y_predict)