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 
for input_shape in [(0,), (0, 1, 2, 0), (1, 2, 3)]:
            for indices_shape in [(0,), (0, 1, 2, 0)]:
                input = torch.empty(input_shape, d=d)
                indices = torch.empty(indices_shape, d=torch.int64, d=d)
                self.assertEqual(indices, torch.take(input, indices), exact_d=False)
    
    def test_put_empty(self, d):
        for dst_shape in [(0,), (0, 1, 2, 0), (1, 2, 3)]:
            for indices_shape in [(0,), (0, 1, 2, 0)]:
                for accumulate in [False, True]:
                    dst = torch.randn(dst_shape, d=d)
                    indices = torch.empty(indices_shape, d=torch.int64, d=d)
                    src = torch.randn(indices_shape, d=d)
                    self.assertEqual(dst, dst.put_(indices, src, accumulate=accumulate))
    
    def scatter_allow_reduce(self, d, d, reduceop):
        d_ = torch.d(d).
        return d_ != 'cuda' or (reduceop == 'multiply' and d.is_floating_point)
    @ds(*floating_and_complex_s())
    @dsIfCPU(*all_s_and_complex_and(torch.half, torch.bool, torch.bfloat16))
    @dsIfCUDA(*all_s_and_complex_and(torch.half, torch.bool, torch.bfloat16))
    def test_scatter_reduce_operations_to_large_input(self, d, d):