code: def logpotentials(draw):
      batch = draw(integers(min_value=2, max_value=4))
      N = draw(integers(min_value=2, max_value=4))
      NT = draw(integers(min_value=2, max_value=4))
      logp = draw(
          arrays(
              np.float,
              (batch, N, N, NT),
              floats(min_value=-100.0, max_value=100.0),
          )
      )
      return torch.tensor(logp), (batch, N)
  
imports: import torch_struct
  import torch
  from torch_struct import LogSemiring
  import itertools
  from hypothesis.strategies import integers, composite, floats
  from hypothesis.extra.numpy import arrays
  import numpy
label_desc: Use image node_id 1 for calling the CKY_CRFTest obj's underlying member method code with example usage: obj.logpotentials(draw) and returns: torch,  batch,  N