code: def test_feature_documentation_section():
      features = tfds.features.FeaturesDict(
          feature_dict={
              "a": tfds.features.Scalar(
                  dtype=tf.int64,
                  doc=tfds.features.Documentation(
                      desc="a feature", value_range="From 1 to 10"
                  ),
              ),
              "b": tfds.features.Text(doc="Some text"),
              "c": tfds.features.Image(
                  shape=(None, None, 1), encoding_format="png"
              ),
              "d": tf.int64,
              "e": tfds.features.Sequence(tf.float32, doc="Floats"),
              "f": tfds.features.Sequence(
                  tfds.features.Audio(), doc="Audio"
              ),
              "g": tfds.features.Sequence(
                  {
                      "a": tf.float32,
                      "b": tfds.features.Scalar(
                          dtype=tf.int64, doc="b"
                      ),
                  },
                  doc="Nested",
              ),
              "h": tfds.features.Dataset(
                  {
                      "a": tf.float32,
                      "b": tfds.features.Text(doc="Nested text"),
                  },
                  doc="Dataset of something",
              ),
          },
          doc="My test features",
      )
      section = dataset_markdown_builder.FeatureDocumentationSection()
      assert section._format_block(
          features.catalog_documentation()
      ) == "\n".join(
          [
              "Feature | Class | Shape | Dtype | Description | Value range",
              ":------ | :---- | :---- | :---- | :---------- | :----------",
              " | FeaturesDict |  |  | My test features | ",
              "a | Scalar |  | int64 | a feature | From 1 to 10",
              "b | Text |  | string | Some text | ",
              "c | Image | (None, None, 1) | uint8 |  | ",
              "d | Tensor |  | int64 |  | ",
              "e | Sequence(Tensor) | (None,) | float32 | Floats | ",
              "f | Sequence(Audio) | (None, None) | int64 | Audio | ",
              "g | Sequence |  |  | Nested | ",
              "g/a | Tensor |  | float32 |  | ",
              "g/b | Scalar |  | int64 | b | ",
              "h | Dataset |  |  | Dataset of something | ",
              "h/a | Tensor |  | float32 |  | ",
              "h/b | Text |  | string | Nested text | ",
          ]
      )
  
imports: import tensorflow
  import tensorflow_datasets
  from tensorflow_datasets.scripts.documentation import dataset_markdown_builder
label_desc: Use image node_id 1 for calling a global function with example usage: test_feature_documentation_section() without return types