code: def test_batch_second(
      self, N: int, T: int, D: int, batch_first: bool
  ):
      seqbias = SequenceBias(D, batch_first)
      if batch_first:
          x = torch.randn([N, T, D])
      else:
          x = torch.randn([T, N, D])
      self.run_test(x, seqbias, batch_first, ew_compatible=False)
  
file_path: opacus/opacus/tests/grad_samples/sequence_bias_test.py
imports: import hypothesis.strategies
  import torch
  from hypothesis import given, settings
  from opacus.layers import SequenceBias
  from .common import GradSampleHooks_test
label_desc: Use image node_id 1 for calling the SequenceBias_test obj's underlying member method code with example usage: obj.test_batch_second(N, T, D, batch_first) without return types