code: def _rand(min_n=2):
      b = torch.randint(2, 4, (1,))
      N = torch.randint(min_n, 4, (1,))
      M = torch.randint(min_n, 4, (1,))
      N = torch.min(M, N)
      return torch.rand(b, N, M, 3), (b.item(), (N).item())
  
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 2 for calling the AlignmentTest obj's underlying member method code with example usage: obj._rand(min_n) and returns: torch,  b,  N