Releases: activeloopai/deeplake
Releases · activeloopai/deeplake
v3.9.37 🌈
🧭 What's Changed
- Updated versions for 3.9.37 release (#3016) @activesoull
- update client after the creds exchange (#3014) @activesoull
⚙️ Who Contributes
v3.9.36🌈
🧭 What's Changed
- Updated versions for 3.9.36 release (#3013) @activesoull
- update client after the creds exchange (#3014) @activesoull
⚙️ Who Contributes
v4.1.4🌈
Fixed Bugs
- Precondition query downloads additional columns data.
- Fixed credentials update after expiration
- Fix the speed and memory usage of clustered index for large result sets (10k).
- Fashionpedia convert to v4 errors out because of list htype
- Fixed MAXSIM in ascending order query
Added features
v3.9.35 🌈
🧭 What's Changed
- Updated versions for 3.9.35 release (#3008) @activesoull
- fixed storage provider error when the local_cache is specified (#3012) @activesoull
⚙️ Who Contributes
v4.1.3 🌈
v4.1.2 🌈
- 100x search time improvement with MAXSIM for ColPali using pooling
- Fixed deadlock issues with multiprocessing
- Improved core engine stability and performance
v4.1 adds the following major features
- Ability to add linked rows for images, segment masks and binary masks
- Ability to save query views through tagging
- Integration with MMDetection and MMSegmentation
- Autocommit the data at the session exit
- Ability to create dynamic arrays
- Ability to create structures with known schema
v4.1.1 🌈
- Bug fixes in
deeplake.convert
and performance improvements in data ingestion. - Fixed TQL UNION expression for the same source.
- Better support for multiprocessing.
v4.1 adds the following major features
- Ability to add linked rows for images, segment masks and binary masks
- Ability to save query views through tagging
- Integration with MMDetection and MMSegmentation
- Autocommit the data at the session exit
- Ability to create dynamic arrays
- Ability to create structures with known schema
v3.9.34 🌈
🧭 What's Changed
- Updated versions for 3.9.34 release (#3005) @activesoull
- V3 labelbox api export improvements (#3007) @tyesayan
- fix azure view loading (#3006) @activesoull
- Update version for the next release (#3002) @activesoull
- make libdeeplake dependency to always download the latest release (#3004) @activesoull
⚙️ Who Contributes
v3.9.33 🌈
🧭 What's Changed
- Update version for the next release (#3002) @activesoull
- Fixed query result datatests merged class_label tensor's class_names consistent @activesoull
- Make libdeeplake dependency to always download the latest release (#3004) @activesoull
⚙️ Who Contributes
v4.1.0🌈
First major release since v4 announcements. Here's the highlights of what's included:
New Features:
- Ability to add linked rows for images, segment masks and binary masks
- Ability to save query views through tagging
- Integration with MMDetection and MMSegmentation
- Autocommit the data at the session exit
- Ability to create dynamic arrays
- Ability to create structures with known schema
Improvements and fixes:
- Significantly improved dataset load time for large datasets
- Flushing the data in background during ingestion
- Reduced memory usage during ingestion
- Ability to slice the dataset and column by slices, lists and tuples
- Fixed various bugs in query engine, v3-to-v4 conversion flow and data ingestion flow