issue_comments: 769656592

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https://github.com/pydata/xarray/issues/3232#issuecomment-769656592 https://api.github.com/repos/pydata/xarray/issues/3232 769656592 MDEyOklzc3VlQ29tbWVudDc2OTY1NjU5Mg== 98330 2021-01-29T08:26:23Z 2021-01-29T08:26:23Z NONE

I'm starting to suspect not because that would involve data_array being both DataArray and a Torch.Tensor object. It seems what I'm in fact enabling is that DataArray.data is a Torch.Tensor.

some_sum is still a DataArray, which doesn't have a backward method. You could use data_array = xr.DataArray( xr_tsr, coords=dict(a=["a1", "a2", "a3"], b=["b1", "b1"]), dims=["a", "b"], name="dummy", attrs={"grad": xr_tsr.grad, "backward": xr_tsr.backward}, ) and your example should work (I assume you meant .grad not .grid).

 
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