class_docstr: Randomly flip the images left to right with a probability.
  
  Parameters
  ----------
  prob : float
      The probability value to flip the images.
  
  Inputs:
      - **data**: a list of frames with shape [H x W x C]
  
  Outputs:
      - **out**: a list of flipped frames with shape [H x W x C]
class_docstr_tok: ["Randomly","flip","the","images","left","to","right","with","a","probability",".","Parameters","--","--","--","--","--","prob",":","float","The","probability","value","to","flip","the","images",".","Inputs",":","-","*","*","data","*","*",":","a","list","of","frames","with","shape","[","H","x","W","x","C","]","Outputs",":","-","*","*","out","*","*",":","a","list","of","flipped","frames","with","shape","[","H","x","W","x","C","]"]
code: def __init__(self, prob=0.5):
      super(VideoRandomHorizontalFlip, self).__init__()
      self.prob = prob
  
imports: from __future__ import division
  import random
  import math
  import numbers
  import numpy
  from mxnet.gluon import Block
label_desc: Use image node_id 1 to create a new VideoRandomHorizontalFlip object from inherited base classes: Block with example: obj = VideoRandomHorizontalFlip(prob)