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 
size_arg = batch_sizes[:dim] + (n,) + batch_sizes[dim:]
            return make_tensor(size_arg, d=d, d=d, low=None, high=None, noncontiguous=not contig)
        def ref_index_copy(tgt, dim, idx, src):
            for i in range(idx.size(0)):
                idx_dest = dim * (slice(None),) + (idx[i],)
                idx_src = dim * (slice(None),) + (i,)
                tgt[idx_dest] = src[idx_src]
        
        for dest_contig, src_contig, index_contig in product([True, False], repeat=3):
            for other_sizes in ((), (4, 5)):
                for dim in range(len(other_sizes)):
                    dest = make_arg(other_sizes, num_dest, dim, dest_contig)
                    src = make_arg(other_sizes, num_copy, dim, src_contig)
                    idx = torch.randperm(num_dest, d=torch.int64, d=d)[:num_copy]
                    if not index_contig:
                        idx = torch.repeat_interleave(idx, 2, dim=-1)
                        idx = idx[..., ::2]
                    dest2 = dest.clone()
                    dest.index_copy_(dim, idx, src)
                    ref_index_copy(dest2, dim, idx, src)
                    self.assertEqual(dest, dest2)
    
    
    
    @onlyNatDTypes
    @ds(*all_s_and_complex_and(torch.half, torch.bool, torch.bfloat16))
    def test_index_copy_scalars(self, d, d):