code: def plot_lr_find(
      self: Recorder,
      skip_end=5,
      return_fig=True,
      suggestions=None,
      nms=None,
      **kwargs,
  ):
      "Plot the result of an LR Finder test (won't work if you didn't do `learn.lr_find()` before)"
      lrs = self.lrs if skip_end == 0 else self.lrs[:-skip_end]
      losses = self.losses if skip_end == 0 else self.losses[:-skip_end]
      fig, ax = plt.subplots(1, 1)
      ax.plot(lrs, losses)
      ax.set_ylabel("Loss")
      ax.set_xlabel("Learning Rate")
      ax.set_xscale("log")
      if suggestions:
          colors = plt.rcParams["axes.prop_cycle"].by_key()["color"][1:]
          for (val, idx), nm, color in zip(suggestions, nms, colors):
              ax.plot(val, idx, "o", label=nm, c=color)
          ax.legend(loc="best")
  
imports: from __future__ import annotations
  from ..basics import *
  from .tracker import SaveModelCallback
label_desc: Use image node_id 22 for calling a global function with example usage: plot_lr_find(skip_end, return_fig, suggestions, nms) without return types