class_docstr: Combination of transforms for validation.
  Follow the style of https://github.com/facebookresearch/SlowFast/
      (1) short side keep aspect ratio resize
      (2) center crop
      (3) to tensor
      (4) normalize
class_docstr_tok: ["Combination","of","transforms","for","validation",".","Follow","the","style","of","https",":","\/\/github.com\/facebookresearch\/SlowFast\/","(","1",")","short","side","keep","aspect","ratio","resize","(","2",")","center","crop","(","3",")","to","tensor","(","4",")","normalize"]
code: def __init__(
      self, crop_size, short_side, mean, std, max_intensity=255.0
  ):
      super(VideoGroupValTransformV2, self).__init__()
  
      from ...utils.filesystem import try_import_cv2
  
      self.cv2 = try_import_cv2()
      self.height = crop_size[0]
      self.width = crop_size[1]
      self.short_side = short_side
      self.mean = np.asarray(mean).reshape((len(mean), 1, 1))
      self.std = np.asarray(std).reshape((len(std), 1, 1))
      self.max_intensity = max_intensity
  
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 VideoGroupValTransformV2 object from inherited base classes: Block with example: obj = VideoGroupValTransformV2(crop_size, short_side, mean, std, max_intensity)