import tensorflow as tf
from tensorflow.keras.layers import Input, Dense
from tensorflow.keras import Model
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.losses import MeanAbsoluteError
from tensorflow.keras.initializers import Constant
import numpy as np
 
models = []
for i in range(3):
	inp = Input(shape = (2, ))
	outp = Dense(2, use_bias = False, kernel_initializer = Constant(0.5))(inp)
	models.append(Model(inputs = inp, outputs = outp))
opts = [Adam(0.1)] * len(models)
# opts = [Adam(0.1) for _ in range(len(models))]
[m.compile(loss = MeanAbsoluteError(), optimizer = o) for m, o in zip(models, opts)]
 
x_data = np.asarray([[1., 2.]])
print(x_data)
y_data = np.asarray([[2., 2.5]])
print(y_data)
print('-'*5)
for m in models:
	pred = m.predict(x_data)
	print(pred)
 
for i in range(3):
	print('-'*5)
	for m in models:
		m.fit(x_data, y_data, verbose = 0)
		pred = m.predict(x_data)
		print(pred)

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