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I would like to use datumaro as a standard dataset format, but in order to use it for pytorch I need to create a pytorch.Dataset wrapper for it. The dataset interface requires to implement the __getitem__(idx:int) function, which is not available on a datumaro dataset.
I am currently using the code from datumaro.FrameworkConverter, which keeps a list of item ids in a list and use indexes from this list. However, once it is converted this way, I can no longer use datumaro dataset manipulation utilities such as split and merge.
Would it be possible to get access to an integer __getitem__ function directly on the datumaro dataset ?
The text was updated successfully, but these errors were encountered:
We plan to incorporate the mentioned __getitem__ functionality into the Datumaro Dataset. Once this feature is implemented, you will be able to retrieve datasetitem within the dataset using an index as you desire. I will provide further updates once this enhancement is included in the release.
Dear @CourchesneA, as following your suggestion, we have implemented random accessing method with __getitem__ at #1247. This will be publicly released with Datumaro 2.0 at the mid of March. Sincerely thank you for your continued interests and suggestions.
I would like to use datumaro as a standard dataset format, but in order to use it for pytorch I need to create a pytorch.Dataset wrapper for it. The dataset interface requires to implement the
__getitem__(idx:int)
function, which is not available on a datumaro dataset.I am currently using the code from datumaro.FrameworkConverter, which keeps a list of item ids in a list and use indexes from this list. However, once it is converted this way, I can no longer use datumaro dataset manipulation utilities such as
split
andmerge
.Would it be possible to get access to an integer
__getitem__
function directly on the datumaro dataset ?The text was updated successfully, but these errors were encountered: