code: def test_forward_doesnt_raise_with_empty_sequence(self):
      # size: (batch_size=1, sequence_length=2, emb_dim=2)
      sequence_tensor = torch.FloatTensor([[[0.0, 0.0], [0.0, 0.0]]])
      # size: (batch_size=1, sequence_length=2)
      sequence_mask = torch.tensor([[False, False]])
      # size: (batch_size=1, spans_count=1, 2)
      span_indices = torch.LongTensor([[[-1, -1]]])
      # size: (batch_size=1, spans_count=1)
      span_indices_mask = torch.tensor([[False]])
      extractor = BidirectionalEndpointSpanExtractor(
          input_dim=2,
          forward_combination="x,y",
          backward_combination="x,y",
      )
      span_representations = extractor(
          sequence_tensor,
          span_indices,
          sequence_mask=sequence_mask,
          span_indices_mask=span_indices_mask,
      )
      numpy.testing.assert_array_equal(
          span_representations.detach(),
          torch.FloatTensor([[[0.0, 0.0, 0.0, 0.0]]]),
      )
  
file_path: allennlp/tests/modules/span_extractors/bidirectional_endpoint_span_extractor_test.py
imports: import numpy
  import pytest
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.params import Params
  from allennlp.modules.span_extractors import BidirectionalEndpointSpanExtractor, SpanExtractor
  from allennlp.nn.util import batched_index_select
label_desc: Use image node_id 5 for calling the TestBidirectonalEndpointSpanExtractor obj's underlying member method code with example usage: obj.test_forward_doesnt_raise_with_empty_sequence() without return types