original_docstring: 
      Calculate districution and predict/sample labels
      Add to lstm_IO
      
docstring: Calculate districution and predict/sample labels
  Add to lstm_IO
docstring_tokens: Calculate districution and predict / sample labels Add to lstm_IO
code: def pass_embed_postprocess(h, embed_out_layer, embed_layer, tree, treelstm_io, is_training):
      """
      Calculate districution and predict/sample labels
      Add to lstm_IO
      """
      pred_dist = embed_out_layer(h)
      label_to_embed = F.softmax(pred_dist.view(-1), 0)[1:].max(0)[1] + 1
      if is_training:
          sampled_label = F.softmax(pred_dist.view(-1), 0)[1:].multinomial(1).detach() + 1
          tree.embeded_label = embed_layer(sampled_label + 1)
      else:
          tree.embeded_label = embed_layer(label_to_embed + 1)
  
      if treelstm_io.dists is None:
          treelstm_io.dists = pred_dist.view(1, -1)
      else:
          treelstm_io.dists = torch.cat((treelstm_io.dists, pred_dist.view(1, -1)), 0)
  
      if treelstm_io.commitments is None:
          treelstm_io.commitments = label_to_embed.view(-1)
      else:
          treelstm_io.commitments = torch.cat((treelstm_io.commitments, label_to_embed.view(-1)), 0)
code_tokens: def pass_embed_postprocess ( h , embed_out_layer , embed_layer , tree , treelstm_io , is_training ) : pred_dist = embed_out_layer ( h ) label_to_embed = F . softmax ( pred_dist . view ( - 1 ) , 0 ) [ 1 : ] . max ( 0 ) [ 1 ] + 1 if is_training : sampled_label = F . softmax ( pred_dist . view ( - 1 ) , 0 ) [ 1 : ] . multinomial ( 1 ) . detach ( ) + 1 tree . embeded_label = embed_layer ( sampled_label + 1 ) else : tree . embeded_label = embed_layer ( label_to_embed + 1 ) if treelstm_io . dists is None : treelstm_io . dists = pred_dist . view ( 1 , - 1 ) else : treelstm_io . dists = torch . cat ( ( treelstm_io . dists , pred_dist . view ( 1 , - 1 ) ) , 0 ) if treelstm_io . commitments is None : treelstm_io . commitments = label_to_embed . view ( - 1 ) else : treelstm_io . commitments = torch . cat ( ( treelstm_io . commitments , label_to_embed . view ( - 1 ) ) , 0 )
short_docstring: Calculate districution and predict/sample labels
  Add to lstm_IO
short_docstring_tokens: Calculate districution and predict / sample labels Add to lstm_IO
comment: """
      Calculate districution and predict/sample labels
      Add to lstm_IO
      """