code: def linear_curriculum(start: int, end: int, period: int) -> Tensor:
      """This function implements linear curriculum
  
      Args:
          start: the starting value for the set of points
          end: the ending value for the set of points
          period: size of the constructed tensor
  
      Returns:
          A float tensor of length period
      """
      return torch.linspace(
          start=start, end=end, steps=period + 1, dtype=torch.float
      )
  
file_path: ml-cvnets/loss_fn/neural_augmentation.py
imports: import argparse
  import math
  from typing import List, Mapping, Union
  import torch
  from torch import Tensor
  from torch.nn import functional
  from loss_fn import LOSS_REGISTRY, BaseCriteria
  from utils import logger
  from utils.ddp_utils import is_master
label_desc: Use image node_id 1 for calling a global function with example usage: linear_curriculum(start, end, period) and returns: torch