class_docstr: A model guaranteed to throw a runtime error, so we can check that native framework errors are
  surfaced properly.
class_docstr_tok: ["A","model","guaranteed","to","throw","a","runtime","error",",","so","we","can","check","that","native","framework","errors","are","surfaced","properly","."]
code: def build_model(self) -> Any:
      model = keras.Sequential([keras.layers.Dense(10)])
      model = self.context.wrap_model(model)
      model.compile(
          # TODO MLG-443 Migrate from legacy Keras optimizers
          optimizer=tf.keras.optimizers.legacy.Adam(name="Adam"),
          loss=tf.keras.losses.SparseCategoricalCrossentropy(
              from_logits=True
          ),
          metrics=[
              tf.keras.metrics.Accuracy()
          ],  # ERR: this is the wrong accuracy, should be SparseCategoricalAccuracy
      )
      return model
  
file_path: determined/harness/tests/experiment/fixtures/tf_keras_runtime_error.py
imports: from typing import Any
  import numpy
  import tensorflow
  from tensorflow import keras
  import determined
  import determined.keras
label_desc: Use image node_id 2 for calling the RuntimeErrorTrial obj's underlying member method code with example usage: obj.build_model() and returns: model