class_docstr: ```
  Abstract class used to tune and train Keras models. The fit method is
  an abstract method and must be implemented by subclasses.
  ```
class_docstr_tok: ["``","`","Abstract","class","used","to","tune","and","train","Keras","models",".","The","fit","method","is","an","abstract","method","and","must","be","implemented","by","subclasses",".","``","`"]
docstr: ```
  View observations with top losses in validation set.
  Musta be overridden by Learner subclasses.
  ```
docstr_tok: ["``","`","View","observations","with","top","losses","in","validation","set",".","Musta","be","overridden","by","Learner","subclasses",".","``","`"]
code: def view_top_losses(self, n=4, preproc=None, val_data=None):
      """
      ```
      View observations with top losses in validation set.
      Musta be overridden by Learner subclasses.
      ```
      """
      raise NotImplementedError(
          "view_top_losses must be overriden by Learner subclass"
      )
  
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 9 for calling the Learner obj's underlying member method code with example usage: obj.view_top_losses(n, preproc, val_data) without return types