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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _activation_summary(x):
 """Helper to create summaries for activations. Creates a summary that provides a histogram of activations. Creates a summary that measures the sparsity of activations. Args: x: Tensor Returns: nothing """

  # Remove 'tower_[0-9]/' from the name in case this is a multi-GPU training
  # session. This helps the clarity of presentation on tensorboard.
  tensor_name = re.sub('%s_[0-9]*/' % TOWER_NAME, '', x.op.name)
  tf.summary.histogram(tensor_name + '/activations', x)
  tf.summary.scalar(tensor_name + '/sparsity',
                                       tf.nn.zero_fraction(x))