google-deepmind / google-deepmind/torch-hdf5
Support for partial writing
- Dominant language
- Lua
- Stars
- 241
- Forks
- 125
- PR merge metrics
- No merged PRs in 30d
Description
In the docs there is a section on partial reading:
``` lua
local myFile = hdf5.open('/path/to/read.h5','r')
-- Specify the range for each dimension of the dataset.
local data = f:read('/path/to/data'):partial({start1, end1}, {start2, end2})
myFile:close()
```
it would be great if there was also support for partial writing, when making datasets that don't fit in RAM. For instance, ideally something along the lines
``` lua
local data = f:write('/path/to/data', data):partial({start1, end1}, {start2, end2})
```
I don't believe this is currently supported, or at least it's not documented in the docs.
Contributor guide
Research direction
Start with the documentation section and existing partial-reading API shown in the issue, then inspect the repository for the corresponding write path. Determine whether partial writing already exists but is undocumented or requires new support; done means the intended partial-write behavior is implemented and documented, with coverage for datasets that are written in ranges.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- lua
- Domain
- data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100