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  1. import tensorflow as tf
  2.  
  3. # Erstellen der Trainingsdaten
  4. inputMuster = [2,3,5,7,10]
  5. outputMuster = [4,5,7,9,12]
  6.  
  7. # Aufbau des neuronalen Netzwerkes
  8. model = tf.keras.Sequential()
  9. model.add(tf.keras.layers.Dense(1, input_shape=[1]))
  10. model.compile(optimizer='sgd', loss='mean_squared_error')
  11.  
  12. # trainieren des neuronalen Netzwerkes
  13. model.fit(inputMuster, outputMuster, epochs=20)
  14.  
  15. # Testen des neuronalen Netzwerkes mit Testdaten
  16. # Model mit vielen Werten testen
  17. test = 1
  18. while test < 21:
  19.   testMuster = [test]
  20.   print(model.predict(testMuster))
  21.   test = test + 1
Success #stdin #stdout #stderr 1.36s 212864KB
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stdin
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Standard input is empty
stdout
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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
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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.
https://ideone.com/tsCpf2
language:
Python (cpython 2.7.16)
created:
1 year ago
visibility:
public

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