text: Problem :
  I am new to Python and Tensorflow so I just simply typed the following code :
  import tensorflow as tf
  print(tf.__version__)
  # Build a dataflow graph.
  c = tf.constant([[1.0, 2.0], [3.0, 4.0]])
  d = tf.constant([[1.0, 1.0], [0.0, 1.0]])
  e = tf.matmul(c, d)
  # Constructing a `Session` to execute the graph.
  sess = tf.compat.v1.Session()
  # Executing the graph and storing the value that `e` represents in `result`.
  result = sess.run(e)
  But it is giving me following error:
  2.0.0-beta1
  I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
  Traceback (most recent call last):
  File "/Users/yupng/Documents/Dissertation/kmnist/kminst_v1.0.py", line 14, in <module>
  result = sess.run(e)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 950, in run
  run_metadata_ptr)
  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1098, in _run
  raise RuntimeError('The Session graph is empty. Add operations to the '
  RuntimeError: The Session graph is empty. Add operations to the graph before calling run().
  Process finished with exit code 1
  How can I fix this error?
  The TF 2.0 supports eager execution it means you need not explicitly create the session and run the code in it. So the simplest solution is as follows:
  # Building a dataflow graph.
  print(e)
  The output as below:
  tf.Tensor(
  [[1. 3.]
  [3. 7.]], shape=(2, 2), dtype=float32)
  But if you want you can use the session as follows:
  with tf.compat.v1.Session() as sess:
  # Build a dataflow graph.
  c = tf.constant([[1.0, 2.0], [3.0, 4.0]])
  d = tf.constant([[1.0, 1.0], [0.0, 1.0]])
  e = tf.matmul(c, d)
  # Executing the graph and storing the value that `e` represents in `result
  result = sess.run(e)
  print(result)
  which gives
  [3. 7.]]