class_docstr: A dataset class to generate random poses.
class_docstr_tok: ["A","dataset","class","to","generate","random","poses","."]
docstr: Update the dataset at the beginning of each epoch.
  
  Parameters:
      epoch (int): Current epoch.
      global_step (int): Current global step.
docstr_tok: ["Update","the","dataset","at","the","beginning","of","each","epoch",".","Parameters",":","epoch","(","int",")",":","Current","epoch",".","global_step","(","int",")",":","Current","global","step","."]
code: def update_step(self, epoch: int, global_step: int) -> None:
      """
      Update the dataset at the beginning of each epoch.
  
      Parameters:
          epoch (int): Current epoch.
          global_step (int): Current global step.
  
      """
      if self.progressive_view:
          self.progressive_view_update_step(global_step=global_step)
  
file_path: NeMo/nemo/collections/multimodal/data/nerf/random_poses.py
imports: import random
  from typing import Any, Dict, Iterator, List, Optional, Tuple
  import numpy
  import torch
  import torch.nn.functional
  from torch.utils.data import IterableDataset
  from nemo.collections.multimodal.data.nerf.cameras import PinholeCamera
  from nemo.collections.multimodal.data.nerf.utils import compute_look_at_vectors, construct_poses, get_rays, get_view_direction
label_desc: Use image node_id 2 for calling the RandomPosesDataset obj's underlying member method code with example usage: obj.update_step(epoch, global_step) without return types