Platforms: linux

This test was disabled because it is failing on master ([recent examples](http://torch-ci.com/failure/test_torch.py%3A%3ATestTorch%3A%3Atest_equal)).

The cause seems to point to https://github.com/pytorch/pytorch/pull/100024 (or D45282119 as it was landed internally)

cc @mruberry @houseroad @ezyang 
yield b1, b2
            # zero-s
            for z1, z2, z3, z4 in itertools.product((True, False), repeat=4):
                shape1 = (num_batches if z1 else 0, M if z2 else 0, N if z3 else 0)
                shape2 = (num_batches if z1 else 0, N if z3 else 0, O if z4 else 0)
                b1 = torch.randn(shape1, d=d, d=d)
                b2 = torch.randn(shape2, d=d, d=d)
                yield b1, b2
        try:
            for num_batches in batch_sizes:
                for (b1, b2), perm3 in itertools.product(generate_inputs(num_batches), itertools.permutations((0, 1, 2))):
                    res1 = torch.bmm(b1, b2)
                    res2 = torch.full((num_batches, M, O), math.nan, d=d, d=d) \
                        .permute(perm3).contiguous().permute(invert_perm(perm3))
                    torch.bmm(b1, b2, out=res2)
                    expect = torch.from_numpy(
                        b1.to(numpy_d).cpu().numpy() @ b2.to(numpy_d).cpu().numpy()).to(d=d, d=d)
                    self.assertEqual(expect, res1)
                    self.assertEqual(expect, res2)
        finally:
            torch.set_num_threads(num_threads)
    def test_conj_neg_tolist(self):
        x = torch.randn(2, d=torch.cfloat)
        y1 = x.conj()
        y1_expect = x.conj_physical()
        y2 = y1.imag
        self.assertEqual(y1, y1_expect.tolist())
        self.assertEqual(y2, y1_expect.imag.tolist())
    @unittest.skipIf(torch.backends.cuda.is_built(), "Skipped for cuda-enabled build")
    def test_no_cuda_monkeypatch(self):