Preserve dtype for numpy/torch/tf/jax arrays
Hi @lhoestq, 
It turns out that pyarrow `ListArray` are not recognized as list-like when we get output from `numpy_to_pyarrow_listarray`. This might cause tests to fail. If possible can we convert that `ListArray` output to list inorder for tests to pass? Under the hood it'll maintain the dtype as that of numpy array passed during input only Brought down the failing tests from 7 to 4. Let me know if that part looks good. Failing tests are looking quite similar. In `test_map_torch` https://github.com/huggingface/datasets/blob/3d46bc384f811435e59e3916faa3aa20a1cf87bc/tests/test_arrow_dataset.py#L1039 and `test_map_tf`https://github.com/huggingface/datasets/blob/3d46bc384f811435e59e3916faa3aa20a1cf87bc/tests/test_arrow_dataset.py#L1056 
they're expecting `float64`. Shouldn't that be `float32` now? It's normal: pytorch and tensorflow use `float32` by default, unlike numpy which uses `float64`.

I think that we should always keep the precision of the original tensor (torch/tf/numpy).
It means that as it is in this PR it's fine (the precision is conserved when doing the torch/tf -> numpy conversion).

This is a breaking change but in my opinion the fact that we had Value("float64") for torch.float32 tensors was an issue already.

Let me know what you think. Cc @albertvillanova if you have an opinion on this

If we agree on doing this breaking change, we can just change the test.  Hi @lhoestq, 
Merged master into this branch. Only changing the test is left for now (mentioned below) after which all tests should pass.

> Brought down the failing tests from 7 to 4. Let me know if that part looks good. Failing tests are looking quite similar. In `test_map_torch`
> 
> https://github.com/huggingface/datasets/blob/3d46bc384f811435e59e3916faa3aa20a1cf87bc/tests/test_arrow_dataset.py#L1039
> 
> and `test_map_tf`
> https://github.com/huggingface/datasets/blob/3d46bc384f811435e59e3916faa3aa20a1cf87bc/tests/test_arrow_dataset.py#L1056
> 
> 
> they're expecting `float64`. Shouldn't that be `float32` now?

 > they're expecting float64. Shouldn't that be float32 now?

Yes feel free to update those tests :)

It would be nice to have the same test for JAX as well Added same test for for JAX too. Also, I saw that I missed changing `test_cast_to_python_objects_jax` like I did for TF and PyTorch. Finished that as well
Fixes #625. This lets the user preserve the dtype of numpy array to pyarrow array which was getting lost due to conversion of numpy array -> list -> pyarrow array. 