pandas df loading tutorial: Fix incorrect super().__init__() call

[vaharoni]

In the beginner's tutorials > load and process data > pandas.DataFrame there is the following code:

class MyModel(tf.keras.Model):
  def __init__(self):
    # Create all the internal layers in init.
    super().__init__(self)

    self.normalizer = tf.keras.layers.Normalization(axis=-1)
    # ...

It seems like super().__init__(self) is incorrect here, sending self as one of the args to the base class tf.keras.Model. The documentation of tf.keras.Model uses super().__init__(), so I suggest to align it.

[github-actions]

Preview

Preview and run these notebook edits with Google Colab:

• site/en/tutorials/load_data/pandas_dataframe.ipynb

Rendered notebook diffs available on ReviewNB.com.

Format and style

Use the TensorFlow docs notebook tools to format for consistent source diffs and lint for style:

$ python3 -m pip install -U --user git+https://github.com/tensorflow/docs

$ python3 -m tensorflow_docs.tools.nbfmt notebook.ipynb

$ python3 -m tensorflow_docs.tools.nblint --arg=repo:tensorflow/docs notebook.ipynb

If commits are added to the pull request, synchronize your local branch: git pull origin tutorial_load_pandas_fix

[MarkDaoust]

Thanks.

Yeah, how does that pass our tests?