class_docstr: `SVHN <http://ufldl.stanford.edu/housenumbers/>`_ Cropped Digit Dataset.
  Produces [img, label], img of 32x32x3 in range [0,255], label of 0-9
class_docstr_tok: ["`","SVHN","<","http",":","\/\/ufldl.stanford.edu\/housenumbers\/",">","`","_","Cropped","Digit","Dataset",".","Produces","[","img",",","label","]",",","img","of","32x32x3","in","range","[","0,255","]",",","label","of","0-9"]
docstr: Args:
      names (tuple[str]): names of the dataset split
  
  Returns:
      a 32x32x3 image, the mean of all images in the given datasets
docstr_tok: ["Args",":","names","(","tuple","[","str","]",")",":","names","of","the","dataset","split","Returns",":","a","32x32x3","image",",","the","mean","of","all","images","in","the","given","datasets"]
code: def get_per_pixel_mean(names=("train", "test", "extra")):
      """
      Args:
          names (tuple[str]): names of the dataset split
  
      Returns:
          a 32x32x3 image, the mean of all images in the given datasets
      """
      for name in names:
          assert name in ["train", "test", "extra"], name
      images = [SVHNDigit(x).X for x in names]
      return np.concatenate(tuple(images)).mean(axis=0)
  
file_path: tensorpack/tensorpack/dataflow/dataset/svhn.py
imports: import numpy
  import os
  from ...utils import logger
  from ...utils.fs import download, get_dataset_path
  from ..base import RNGDataFlow
label_desc: Use image node_id 4 for calling the SVHNDigit obj's underlying member method code with example usage: obj.get_per_pixel_mean(names) and returns: np