class_docstr: ```
  Abstract class used to tune and train Keras models. The fit method is
  an abstract method and must be implemented by subclasses.
  ```
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docstr: ```
  Return numerical estimates of lr using two different methods:
    1. lr associated with minum numerical gradient (None if gradient computation fails)
    2. lr associated with minimum loss divided by 10
    3. lr associated with longest valley
  Since none of these methods are fool-proof and can
  potentially return bad estimates, it is recommended that you
  examine the plot generated by lr_plot to estimate the learning rate.
  Returns:
    tuple: tuple of the form (float, float)
  ```
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code: def lr_estimate(self):
      """
      ```
      Return numerical estimates of lr using two different methods:
        1. lr associated with minum numerical gradient (None if gradient computation fails)
        2. lr associated with minimum loss divided by 10
        3. lr associated with longest valley
      Since none of these methods are fool-proof and can
      potentially return bad estimates, it is recommended that you
      examine the plot generated by lr_plot to estimate the learning rate.
      Returns:
        tuple: tuple of the form (float, float)
      ```
      """
      if self.lr_finder is None or not self.lr_finder.find_called():
          raise ValueError("Please call lr_find first.")
      return self.lr_finder.estimate_lr()
  
imports: from .None import utils
  from .graph.predictor import LinkPredictor, NodePredictor
  from .graph.preprocessor import LinkPreprocessor, NodePreprocessor
  from .imports import *
  from .lroptimize.lrfinder import *
  from .tabular.predictor import TabularPredictor
  from .tabular.preprocessor import TabularPreprocessor
  from .text.ner.predictor import NERPredictor
  from .text.ner.preprocessor import NERPreprocessor
  from .text.predictor import TextPredictor
  from .text.preprocessor import BERTPreprocessor, TextPreprocessor, TransformersPreprocessor
  from .vision.predictor import ImagePredictor
  from .vision.preprocessor import ImagePreprocessor
label_desc: Use image node_id 20 for calling the Learner obj's underlying member method code with example usage: obj.lr_estimate() and returns: self