message: Updated line for creating global step + grammar
  tf.train.get_global_step() returns None if there is no global step, preventing the pruning from working. Therefore, tf.train.get_or_create_global_step() is a safer option.
diff: @@ -66,10 +66,10 @@ is the sparsity_function_begin_step. In this equation, the
  sparsity_function_exponent is set to 3.
  ### Adding pruning ops to the training graph
  -The final step involves adding ops to the training graph that monitors the
  -distribution of the layer's weight magnitudes and determines the layer threshold
  -such masking all the weights below this threshold achieves the sparsity level
  -desired for the current training step. This can be achieved as follows:
  +The final step involves adding ops to the training graph that monitor the
  +distribution of the layer's weight magnitudes and determine the layer threshold,
  +such that masking all the weights below this threshold achieves the sparsity
  +level desired for the current training step. This can be achieved as follows:
  ```python
  tf.app.flags.DEFINE_string(
  @@ -79,7 +79,7 @@ tf.app.flags.DEFINE_string(
  with tf.graph.as_default():
  # Create global step variable
  - global_step = tf.train.get_global_step()
  + global_step = tf.train.get_or_create_global_step()
  # Parse pruning hyperparameters
  pruning_hparams = pruning.get_pruning_hparams().parse(FLAGS.pruning_hparams)
  