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  1. import tensorflow as tf
  2.  
  3. # Erstellen der Trainingsdaten
  4. inputMuster = [2, 16, 48]
  5. outputMuster= [4, 32, 96]
  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. testMuster = [22]
  17. print(model.predict(testMuster))
Success #stdin #stdout #stderr 1.41s 213116KB
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stdin
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Standard input is empty
stdout
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Epoch 1/20

3/3 [==============================] - 0s 42ms/sample - loss: 4465.2866
Epoch 2/20

3/3 [==============================] - 0s 330us/sample - loss: 1158117.6250
Epoch 3/20

3/3 [==============================] - 0s 281us/sample - loss: 300369600.0000
Epoch 4/20

3/3 [==============================] - 0s 267us/sample - loss: 77903937536.0000
Epoch 5/20

3/3 [==============================] - 0s 253us/sample - loss: 20205185007616.0000
Epoch 6/20

3/3 [==============================] - 0s 255us/sample - loss: 5240421131223040.0000
Epoch 7/20

3/3 [==============================] - 0s 244us/sample - loss: 1359156763189837824.0000
Epoch 8/20

3/3 [==============================] - 0s 249us/sample - loss: 352511273979961409536.0000
Epoch 9/20

3/3 [==============================] - 0s 250us/sample - loss: 91427395891263344476160.0000
Epoch 10/20

3/3 [==============================] - 0s 246us/sample - loss: 23712636953182021126979584.0000
Epoch 11/20

3/3 [==============================] - 0s 256us/sample - loss: 6150116139975867290903117824.0000
Epoch 12/20

3/3 [==============================] - 0s 243us/sample - loss: 1595095260910041949412272373760.0000
Epoch 13/20

3/3 [==============================] - 0s 239us/sample - loss: 413704318992440386626652620193792.0000
Epoch 14/20

3/3 [==============================] - 0s 242us/sample - loss: 107298452905060335326881592115200000.0000
Epoch 15/20

3/3 [==============================] - 0s 246us/sample - loss: 27828959268617160675890591880789884928.0000
Epoch 16/20

3/3 [==============================] - 0s 241us/sample - loss: inf
Epoch 17/20

3/3 [==============================] - 0s 246us/sample - loss: inf
Epoch 18/20

3/3 [==============================] - 0s 251us/sample - loss: inf
Epoch 19/20

3/3 [==============================] - 0s 241us/sample - loss: inf
Epoch 20/20

3/3 [==============================] - 0s 246us/sample - loss: inf
[[-6.9295217e+25]]
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/icSJp0
language:
Python (cpython 2.7.16)
created:
1 year ago
visibility:
public

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