class_docstr: Layer to generate mask.
docstr: Constructs a mask generator layer.
  
  Args:
    example_feature_columns: (dict) example feature names to columns.
    size_feature_name: (str) Name of feature for example list sizes. If not
      None, this feature name corresponds to a `tf.int32` Tensor of size
      [batch_size] corresponding to sizes of example lists. If `None`, all
      examples are treated as valid.
    name: (str) name of the layer.
    **kwargs: keyword arguments.
docstr_tok: ["Constructs","a","mask","generator","layer",".","Args",":","example_feature_columns",":","(","dict",")","example","feature","names","to","columns",".","size_feature_name",":","(","str",")","Name","of","feature","for","example","list","sizes",".","If","not","None",",","this","feature","name","corresponds","to","a","`","tf.int32","`","Tensor","of","size","[","batch_size","]","corresponding","to","sizes","of","example","lists",".","If","`","None","`",",","all","examples","are","treated","as","valid",".","name",":","(","str",")","name","of","the","layer",".","*","*","kwargs",":","keyword","arguments","."]
code: def __init__(
      self,
      example_feature_columns,
      size_feature_name,
      name="generate_mask_layer",
      **kwargs,
  ):
      """Constructs a mask generator layer.
  
      Args:
        example_feature_columns: (dict) example feature names to columns.
        size_feature_name: (str) Name of feature for example list sizes. If not
          None, this feature name corresponds to a `tf.int32` Tensor of size
          [batch_size] corresponding to sizes of example lists. If `None`, all
          examples are treated as valid.
        name: (str) name of the layer.
        **kwargs: keyword arguments.
      """
      super(GenerateMask, self).__init__(name=name, **kwargs)
      self._example_feature_columns = example_feature_columns
      self._size_feature_name = size_feature_name
  
imports: import six
  import tensorflow.compat.v2
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow_ranking.python import utils
label_desc: Use image node_id 1 to create a new GenerateMask object from inherited base classes: tf.keras.layers with example: obj = GenerateMask(example_feature_columns, size_feature_name, name)