docstr: negative sampling loss.
  Args:
      neg_samples: tensor of shape [num_neg_samples x input_dim2]. Negative samples for all
      inputs in batch inputs1.
docstr_tok: ["negative","sampling","loss",".","Args",":","neg_samples",":","tensor","of","shape","[","num_neg_samples","x","input_dim2","]",".","Negative","samples","for","all","inputs","in","batch","inputs1","."]
code: def loss(self, inputs1, inputs2, neg_samples):
      """negative sampling loss.
      Args:
          neg_samples: tensor of shape [num_neg_samples x input_dim2]. Negative samples for all
          inputs in batch inputs1.
      """
      return self.loss_fn(inputs1, inputs2, neg_samples)
  
file_path: GraphSAGE/graphsage/prediction.py
imports: from __future__ import division
  from __future__ import print_function
  from graphsage.inits import zeros
  from graphsage.layers import Layer
  import tensorflow
label_desc: Use image node_id 4 for calling the BipartiteEdgePredLayer obj's underlying member method code with example usage: obj.loss(inputs1, inputs2, neg_samples) and returns: self