code: def glu(x, axis=-1):
      """
      Gated Linear Unit. Implementation as defined in the original paper (see https://arxiv.org/abs/1612.08083), where
      the input `x` is split in two halves across a dimension (`axis`), A and B, returning A * sigmoid(B).
  
      Args:
          `x`: float Tensor to perform activation
          `axis`: dimension across which `x` be split in half
  
      Returns:
          `x` with the GLU activation applied (with its size halved across the dimension `axis`).
      """
      a, b = tf.split(x, 2, axis=axis)
      return a * tf.math.sigmoid(b)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/activations_tf.py
imports: import math
  import tensorflow
  from packaging import version
label_desc: Use image node_id 7 for calling a global function with example usage: glu(x, axis) and returns: unknown