code: def pixel_norm(images, epsilon=1.0e-8):
      """Pixel normalization.
  
      For each pixel a[i,j,k] of image in HWC format, normalize its value to
      b[i,j,k] = a[i,j,k] / SQRT(SUM_k(a[i,j,k]^2) / C + eps).
  
      Args:
        images: A 4D `Tensor` of NHWC format.
        epsilon: A small positive number to avoid division by zero.
  
      Returns:
        A 4D `Tensor` with pixel-wise normalized channels.
      """
      return images * tf.rsqrt(
          tf.reduce_mean(tf.square(images), axis=3, keepdims=True)
          + epsilon
      )
  
file_path: magenta/magenta/models/gansynth/lib/layers.py
imports: import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: pixel_norm(images, epsilon) and returns: unknown