code: def activation(incoming, activation="linear", name="activation"):
      """Activation.
  
      Apply given activation to incoming tensor.
  
      Arguments:
          incoming: A `Tensor`. The incoming tensor.
          activation: `str` (name) or `function` (returning a `Tensor`).
              Activation applied to this layer (see tflearn.activations).
              Default: 'linear'.
  
      """
  
      if isinstance(activation, str):
          x = activations.get(activation)(incoming)
      elif hasattr(activation, "__call__"):
          x = activation(incoming)
      else:
          raise ValueError("Unknown activation type.")
  
      # Track output tensor.
      tf.add_to_collection(tf.GraphKeys.LAYER_TENSOR + "/" + name, x)
  
      return x
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import tensorflow.compat.v1
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import standard_ops
  import tflearn
  from tflearn import utils
  from tflearn import variables
  from tflearn import activations
  from tflearn import initializations
  from tflearn import regularizers
label_desc: Use image node_id 7 for calling a global function with example usage: activation(incoming, activation, name) and returns: x