class_docstr: Training with exponentially growing learning rate
class_docstr_tok: ["Training","with","exponentially","growing","learning","rate"]
code: def __init__(
      self, start_lr=1e-7, end_lr=10, num_it=100, stop_div=True
  ):
      if num_it < 6:
          num_it = 6
      self.scheds = {
          "lr": [SchedExp(s, e) for (s, e) in zip(start_lr, end_lr)]
          if is_listy(start_lr)
          else SchedExp(start_lr, end_lr)
      }
      self.num_it, self.stop_div = num_it, stop_div
  
imports: from __future__ import annotations
  from ..basics import *
  from .tracker import SaveModelCallback
label_desc: Use image node_id 1 to create a new LRFinder object from inherited base classes: ParamScheduler with example: obj = LRFinder(start_lr, end_lr, num_it, stop_div)