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  1. import tensorflow as tf
  2. import numpy as np
  3.  
  4. # Create 100 phony x, y data points in NumPy, y = x * 0.1 + 0.3
  5. x_data = np.random.rand(100).astype(np.float32)
  6. y_data = x_data * 0.1 + 0.3
  7.  
  8. # Try to find values for W and b that compute y_data = W * x_data + b
  9. # (We know that W should be 0.1 and b 0.3, but TensorFlow will
  10. # figure that out for us.)
  11. W = tf.Variable(tf.random_uniform([1], -1.0, 1.0))
  12. b = tf.Variable(tf.zeros([1]))
  13. y = W * x_data + b
  14.  
  15. # Minimize the mean squared errors.
  16. loss = tf.reduce_mean(tf.square(y - y_data))
  17. optimizer = tf.train.GradientDescentOptimizer(0.5)
  18. train = optimizer.minimize(loss)
  19.  
  20. # Before starting, initialize the variables.  We will 'run' this first.
  21. init = tf.initialize_all_variables()
  22.  
  23. # Launch the graph.
  24. sess = tf.Session()
  25. sess.run(init)
  26.  
  27. # Fit the line.
  28. for step in range(201):
  29.     sess.run(train)
  30.     if step % 20 == 0:
  31.         print(step, sess.run(W), sess.run(b))
  32.  
  33. # Learns best fit is W: [0.1], b: [0.3]# your code goes here
Success #stdin #stdout #stderr 1.2s 211732KB
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stdin
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import tensorflow as tf
Import numpy as np

vector 1 = tf.constant([1.0, 2.0, 3.0])
vector 2 = tf.constant([4.0, 5.0, 6.0]) 
result = tf.add(vector 1, vector 2)
print("Result of vector addition:") print(result.np())
stdout
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(0, array([0.79902035], dtype=float32), array([-0.13770618], dtype=float32))
(20, array([0.28591508], dtype=float32), array([0.19654357], dtype=float32))
(40, array([0.14802471], dtype=float32), array([0.27327564], dtype=float32))
(60, array([0.1124055], dtype=float32), array([0.2930967], dtype=float32))
(80, array([0.10320453], dtype=float32), array([0.2982168], dtype=float32))
(100, array([0.10082779], dtype=float32), array([0.2995394], dtype=float32))
(120, array([0.10021383], dtype=float32), array([0.29988104], dtype=float32))
(140, array([0.10005523], dtype=float32), array([0.2999693], dtype=float32))
(160, array([0.10001427], dtype=float32), array([0.29999205], dtype=float32))
(180, array([0.1000037], dtype=float32), array([0.29999796], dtype=float32))
(200, array([0.10000096], dtype=float32), array([0.29999948], dtype=float32))
stderr
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WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py:263: 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/util/tf_should_use.py:193: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.
Instructions for updating:
Use `tf.global_variables_initializer` instead.
https://ideone.com/wkq3hp
language:
Python (cpython 2.7.16)
created:
2 days ago
visibility:
public

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