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 
[0.999994993209838867187500000, 0.099999502301216125488281250]],
                 [[0.999994993209838867187500000, 0.499997496604919433593750000],
                  [1.499992489814758300781250000, -1.499992489814758300781250000]]]])]
        for i in range(len(inputs)):
            for affine in [False, True]:
                m = torch.nn.BatchNorm2d(inputs[i].size()[1], 1e-05, 0.1, affine=affine)
                m.eval()
                # co
                input1 = inputs[i].contiguous()
                output1 = m(input1)
                # non-co
                input2 = input1.permute(0, 1, 3, 2)
                output2 = m(input2).permute(0, 1, 3, 2)
                # channe
                input3 = input1.contiguous(memory_format=torch.channels_last)
                output3 = m(input3)
                self.assertEqual(output3, outputs[i])
                self.assertEqual(output3, output1)
                self.assertEqual(output3, output2)
    # FIXME: move these meta tests to their own test suite/class or
    #   distribute them among the appropriate test suites for their ops
    @skipIfTorchDynamo("Fails after Triton update, see https://github.com/pytorch/pytorch/issues/94687")
    def test_empty_meta(self):
        x = torch.empty(2 ** 20, 2 ** 20, d='meta')
        y = torch.empty(2 ** 20, d='meta')
        z = x + y
        self.assertEqual(z.size(), (2 ** 20, 2 ** 20))
        self.assertRaises(RuntimeError, lambda: z[0][0].item())
    @skipIfTorchDynamo("Fails after Triton update, see https://github.com/pytorch/pytorch/issues/94687")
    def test_format_scalar_meta(self):