class_docstr: Base class for ranking networks in Keras.
class_docstr_tok: ["Base","class","for","ranking","networks","in","Keras","."]
docstr: Defines the forward pass for ranking model.
  
  Args:
    inputs: (dict) with a mix of context (2D) and example features (3D).
    training: (bool) whether in train or inference mode.
    mask: (tf.Tensor) Mask is a tensor of shape [batch_size, list_size], which
      is True for a valid example and False for invalid one.
  
  Returns:
    (tf.Tensor) A score tensor of shape [batch_size, list_size].
docstr_tok: ["Defines","the","forward","pass","for","ranking","model",".","Args",":","inputs",":","(","dict",")","with","a","mix","of","context","(","2D",")","and","example","features","(","3D",")",".","training",":","(","bool",")","whether","in","train","or","inference","mode",".","mask",":","(","tf.Tensor",")","Mask","is","a","tensor","of","shape","[","batch_size",",","list_size","]",",","which","is","True","for","a","valid","example","and","False","for","invalid","one",".","Returns",":","(","tf.Tensor",")","A","score","tensor","of","shape","[","batch_size",",","list_size","]","."]
code: def call(self, inputs=None, training=None, mask=None):
      """Defines the forward pass for ranking model.
  
      Args:
        inputs: (dict) with a mix of context (2D) and example features (3D).
        training: (bool) whether in train or inference mode.
        mask: (tf.Tensor) Mask is a tensor of shape [batch_size, list_size], which
          is True for a valid example and False for invalid one.
  
      Returns:
        (tf.Tensor) A score tensor of shape [batch_size, list_size].
      """
      context_features, example_features = self.transform(
          features=inputs, training=training, mask=mask
      )
      logits = self.compute_logits(
          context_features=context_features,
          example_features=example_features,
          training=training,
          mask=mask,
      )
      return logits
  
imports: import abc
  import six
  import tensorflow.compat.v2
  from tensorflow_ranking.python import utils
  from tensorflow_ranking.python.keras import feature
label_desc: Use image node_id 6 for calling the RankingNetwork obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: logits