class_docstr: Generate random planckian jitter parameters for a batch of images.
code: def make_samplers(
      self, device: torch.device, dtype: torch.dtype
  ) -> None:
      idx_range = _range_bound(
          self.domain, "idx_range", device=device, dtype=dtype
      )
  
      _joint_range_check(idx_range, "idx_range", (0, self.domain[1]))
      self.pl_idx_dist = UniformDistribution(
          idx_range[0], idx_range[1], validate_args=False
      )
  
file_path: kornia/kornia/augmentation/random_generator/_2d/planckian_jitter.py
imports: from typing import Dict, List, Tuple
  import torch
  from kornia.augmentation.random_generator.base import RandomGeneratorBase, UniformDistribution
  from kornia.augmentation.utils import _adapted_rsampling, _common_param_check, _joint_range_check, _range_bound
label_desc: Use image node_id 2 for calling the PlanckianJitterGenerator obj's underlying member method code with example usage: obj.make_samplers(device, dtype) without return types