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[Prototype] Tools for the concurrent manipulation of variably sized Tensors.

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There should be a way to replace tensors inside of an NT via assigning.

enhancement

Investigate if there is any issue in here.

bug
question

``` a = nt.nested_tensor([ nt.nested_tensor([]), nt.nested_tensor([ torch.tensor([1]) ]) ]) ``` same for cuda should succeed ``` a = nt.nested_tensor([ [], [ torch.tensor([1]) ] ]) ```

bug

Repro: `creation.nested_tensor([]).is_contiguous() != creation.nested_tensor([], dtype=torch.float).is_contiguous()`

bug

I found out that `tensorwise` actually just runs a for loop over the nested tensors. I benchmarked `tensorwise` against `map`, list comprehension and for loop. (Un)surprisingly, `tensorwise` performs much slower...

perf

I got a pickler error in multiprocessing that it cant pickle the nestedtensor object. does it mean i cant use nestedtensor for Dataset? I guess using nestedtensor in Dataset is...

enhancement

As of right now, we are not supporting empty tensors in nested tensor when calling `to_tensor_mask()` method. Example case: ``` nt1 = nt.nested_tensor([ nt.nested_tensor([ nt.nested_tensor([ torch.tensor([], dtype=torch.float) ]), nt.nested_tensor([ torch.tensor([1],...

enhancement