code: def test_make_scipy_linear_constraints(self):
      for shapeX in [torch.Size([2, 1, 4]), torch.Size([1, 4])]:
          b = shapeX[0] if len(shapeX) == 3 else 1
          res = make_scipy_linear_constraints(
              shapeX=shapeX,
              inequality_constraints=None,
              equality_constraints=None,
          )
          self.assertEqual(res, [])
          indices = torch.tensor(
              [0, 1], dtype=torch.long, device=self.device
          )
          coefficients = torch.tensor([1.5, -1.0], device=self.device)
          # both inequality and equality constraints
          cs = make_scipy_linear_constraints(
              shapeX=shapeX,
              inequality_constraints=[(indices, coefficients, 1.0)],
              equality_constraints=[(indices, coefficients, 1.0)],
          )
          self.assertEqual(len(cs), 2 * b)
          self.assertTrue({c["type"] for c in cs} == {"ineq", "eq"})
          # inequality only
          cs = make_scipy_linear_constraints(
              shapeX=shapeX,
              inequality_constraints=[(indices, coefficients, 1.0)],
          )
          self.assertEqual(len(cs), b)
          self.assertTrue(all(c["type"] == "ineq" for c in cs))
          # equality only
          cs = make_scipy_linear_constraints(
              shapeX=shapeX,
              equality_constraints=[(indices, coefficients, 1.0)],
          )
          self.assertEqual(len(cs), b)
          self.assertTrue(all(c["type"] == "eq" for c in cs))
  
          # test that 2-dim indices work properly
          indices = indices.unsqueeze(0)
          cs = make_scipy_linear_constraints(
              shapeX=shapeX,
              inequality_constraints=[(indices, coefficients, 1.0)],
              equality_constraints=[(indices, coefficients, 1.0)],
          )
          self.assertEqual(len(cs), 2 * b)
          self.assertTrue({c["type"] for c in cs} == {"ineq", "eq"})
  
imports: from itertools import product
  from typing import Callable
  import numpy
  import torch
  from botorch.exceptions.errors import CandidateGenerationError, UnsupportedError
  from botorch.optim.parameter_constraints import _arrayify, _generate_unfixed_lin_constraints, _generate_unfixed_nonlin_constraints, _make_linear_constraints, _make_nonlinear_constraints, eval_lin_constraint, lin_constraint_jac, make_scipy_bounds, make_scipy_linear_constraints, make_scipy_nonlinear_inequality_constraints, nonlinear_constraint_is_feasible
  from botorch.utils.testing import BotorchTestCase
  from scipy.optimize import Bounds
label_desc: Use image node_id 7 for calling the TestParameterConstraints obj's underlying member method code with example usage: obj.test_make_scipy_linear_constraints() without return types