import numpy as np

data = np.arange(1, 100)
n = data.shape[0]
piece = 11

xs = []
ys = []
for i in range(n - piece - 1):
 xs += [ data[i:i+piece] ]
 ys += [ data[i+piece] ]
xs = np.array(xs)
ys = np.array(ys)

print (xs, ys)

from tensorflow.keras.models import Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import Adam
input = Input(shape=(piece,) )
x = input
x = Dense(1024)(x)
x = Dense(1)(x)
model = Model(inputs=input, outputs = x)

adam = Adam(learning_rate=5e-4)

model.compile(optimizer=adam, loss='mean_squared_error')

model.fit(xs, ys, epochs=1000, validation_split=0.1)

inp = list(range(1000, 1000+piece))

for i in range(20):
    a = model.predict(np.array([inp],dtype=np.float32))
    print (a[0,0])
    inp = inp[1:] + [a[0,0]]