class_docstr: A fourth-order Improved Pseudo Linear Multistep scheduler.
  
  This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic
  methods the library implements for all schedulers such as loading and saving.
  
  Args:
      num_train_timesteps (`int`, defaults to 1000):
          The number of diffusion steps to train the model.
      trained_betas (`np.ndarray`, *optional*):
          Pass an array of betas directly to the constructor to bypass `beta_start` and `beta_end`.
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docstr: The index counter for current timestep. It will increae 1 after each scheduler step.
docstr_tok: ["The","index","counter","for","current","timestep",".","It","will","increae","1","after","each","scheduler","step","."]
code: def step_index(self):
      """
      The index counter for current timestep. It will increae 1 after each scheduler step.
      """
      return self._step_index
  
file_path: llmga/llmga/diffusers/src/diffusers/schedulers/scheduling_ipndm.py
imports: import math
  from typing import List, Optional, Tuple, Union
  import numpy
  import torch
  from ..configuration_utils import ConfigMixin, register_to_config
  from .scheduling_utils import SchedulerMixin, SchedulerOutput
label_desc: Use image node_id 2 for calling the IPNDMScheduler obj's underlying member method code with example usage: obj.step_index() and returns: self