code: def make_beta_schedule(
      schedule,
      n_timestep,
      linear_start=1e-4,
      linear_end=2e-2,
  ):
      if schedule == "linear":
          betas = (
              torch.linspace(
                  linear_start**0.5,
                  linear_end**0.5,
                  n_timestep,
                  dtype=torch.float64,
              )
              ** 2
          )
      return betas.numpy()
  
imports: import math
  from typing import Optional
  import torch
  import torch.nn
  from einops import rearrange, repeat
label_desc: Use image node_id 1 for calling a global function with example usage: make_beta_schedule(schedule, n_timestep, linear_start, linear_end) and returns: betas