class_docstr: PyOD Dataset class for PyTorch Dataloader
      
code: def __init__(self, X, y=None, mean=None, std=None):
      super(PyODDataset, self).__init__()
      self.X = X
      self.mean = mean
      self.std = std
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  import torch
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from torch import nn
  from .base import BaseDetector
  from ..utils.stat_models import pairwise_distances_no_broadcast
  from ..utils.torch_utility import get_activation_by_name
label_desc: Use image node_id 1 to create a new PyODDataset object from inherited base classes: torch.utils.data with example: obj = PyODDataset(X, y, mean, std)