class_docstr: A fake, ImageNet-like dataset which only actually contains `num_actual_datapoints` independent
  datapoints, but pretends to have the number reported in `__len__`. Used for speed and
  simplicity. Replace with your own ImageNet-like dataset as desired.
class_docstr_tok: ["A","fake",",","ImageNet-like","dataset","which","only","actually","contains","`","num_actual_datapoints","`","independent","datapoints",",","but","pretends","to","have","the","number","reported","in","`","__len__","`",".","Used","for","speed","and","simplicity",".","Replace","with","your","own","ImageNet-like","dataset","as","desired","."]
code: def __len__(self) -> int:
      return 10**6
  
imports: from typing import Any, Dict
  import deepspeed
  import torch
  import torch.nn
  from attrdict import AttrDict
  from torch.utils.data import Dataset
  from torchvision import models
  from determined.pytorch import DataLoader, dsat
  from determined.pytorch.deepspeed import DeepSpeedTrial, DeepSpeedTrialContext
label_desc: Use image node_id 2 for calling the RandImageNetDataset obj's underlying member method code with example usage: obj.__len__() and returns: unknown