message: Api doc fixit: Add executable example in `tf.keras.layers.Dense` and argument list in `__init__`.
diff: @@ -56,6 +56,7 @@ from tensorflow.python.util import tf_inspect
  from tensorflow.python.util.tf_export import keras_export
  +# pylint: disable=g-classes-have-attributes
  @keras_export('keras.layers.Masking')
  class Masking(Layer):
  """Masks a sequence by using a mask value to skip timesteps.
  @@ -1072,17 +1073,17 @@ class Dense(Layer):
  Example:
  - ```python
  - # as first layer in a sequential model:
  - model = Sequential()
  - model.add(Dense(32, input_shape=(16,)))
  - # now the model will take as input arrays of shape (*, 16)
  - # and output arrays of shape (*, 32)
  -
  - # after the first layer, you don't need to specify
  - # the size of the input anymore:
  - model.add(Dense(32))
  - ```
  + >>> # Create a `Sequential` model and add a Dense layer as the first layer.
  + >>> model = tf.keras.models.Sequential()
  + >>> model.add(tf.keras.Input(shape=(16,)))
  + >>> model.add(tf.keras.layers.Dense(32, activation='relu'))
  + >>> # Now the model will take as input arrays of shape (None, 16)
  + >>> # and output arrays of shape (None, 32).
  + >>> # Note that after the first layer, you don't need to specify
  + >>> # the size of the input anymore:
  + >>> model.add(tf.keras.layers.Dense(32))
  + >>> model.output_shape
  + (None, 32)
  Arguments:
  units: Positive integer, dimensionality of the output space.
  