import tensorflow as tf
# Erstellen der Trainingsdaten
inputMuster = [ 2 , 3 , 5 , 7 , 10 ]
outputMuster = [ 4 , 5 , 7 , 9 , 12 ]
# Aufbau des neuronalen Netzwerkes
model = tf.keras .Sequential ( )
model.add ( tf.keras .layers .Dense ( 1 , input_shape= [ 1 ] ) )
model.compile ( optimizer= 'sgd' , loss= 'mean_squared_error' )
# trainieren des neuronalen Netzwerkes
model.fit ( inputMuster, outputMuster, epochs= 20 )
# Testen des neuronalen Netzwerkes mit Testdaten
# Model mit vielen Werten testen
test = 1
while test < 21 :
testMuster = [ test ]
print ( model.predict ( testMuster) )
test = test + 1
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stdout
Epoch 1/20
5/5 [==============================] - 0s 21ms/sample - loss: 106.7864
Epoch 2/20
5/5 [==============================] - 0s 166us/sample - loss: 6.6024
Epoch 3/20
5/5 [==============================] - 0s 150us/sample - loss: 1.0021
Epoch 4/20
5/5 [==============================] - 0s 147us/sample - loss: 0.6839
Epoch 5/20
5/5 [==============================] - 0s 146us/sample - loss: 0.6607
Epoch 6/20
5/5 [==============================] - 0s 145us/sample - loss: 0.6540
Epoch 7/20
5/5 [==============================] - 0s 142us/sample - loss: 0.6483
Epoch 8/20
5/5 [==============================] - 0s 142us/sample - loss: 0.6428
Epoch 9/20
5/5 [==============================] - 0s 145us/sample - loss: 0.6372
Epoch 10/20
5/5 [==============================] - 0s 148us/sample - loss: 0.6317
Epoch 11/20
5/5 [==============================] - 0s 145us/sample - loss: 0.6263
Epoch 12/20
5/5 [==============================] - 0s 143us/sample - loss: 0.6209
Epoch 13/20
5/5 [==============================] - 0s 141us/sample - loss: 0.6156
Epoch 14/20
5/5 [==============================] - 0s 144us/sample - loss: 0.6102
Epoch 15/20
5/5 [==============================] - 0s 147us/sample - loss: 0.6050
Epoch 16/20
5/5 [==============================] - 0s 144us/sample - loss: 0.5998
Epoch 17/20
5/5 [==============================] - 0s 142us/sample - loss: 0.5946
Epoch 18/20
5/5 [==============================] - 0s 142us/sample - loss: 0.5895
Epoch 19/20
5/5 [==============================] - 0s 144us/sample - loss: 0.5844
Epoch 20/20
5/5 [==============================] - 0s 147us/sample - loss: 0.5794
[[1.6199219]]
[[2.8543913]]
[[4.0888605]]
[[5.32333]]
[[6.5577993]]
[[7.7922688]]
[[9.026738]]
[[10.261208]]
[[11.495677]]
[[12.730146]]
[[13.964616]]
[[15.199085]]
[[16.433556]]
[[17.668024]]
[[18.902493]]
[[20.136963]]
[[21.371433]]
[[22.605902]]
[[23.84037]]
[[25.07484]]
stderr
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/keras/utils/losses_utils.py:170: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.