feature_column.py 文件源码

def to_weighted_sum(self,
                      input_tensor,
                      num_outputs=1,
                      weight_collections=None,
                      trainable=True):

    def _weight(name):
      return variable_scope.get_variable(
          name,
          shape=[self.dimension, num_outputs],
          initializer=init_ops.zeros_initializer,
          collections=_add_variable_collection(weight_collections))

    if self.name:
      weight = _weight("weight")
    else:
      # Old behavior to support a subset of old checkpoints.
      weight = _weight("_weight")

    # The _RealValuedColumn has the shape of [batch_size, column.dimension].
    log_odds_by_dim = math_ops.matmul(input_tensor, weight, name="matmul")
    return log_odds_by_dim, [weight]