[FEA] search_multi_cta_00_generate.py support cuvs::neighbors::filtering::bitmap_filter<uint32_t COMMA int64_t>
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Description
Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I wish I could use RAFT to do [...]
I wish I could use RAFT to support batch queries with filtering. and each query has its own bitset
Describe the solution you'd like
in search_multi_cta.*.cu, add the code like following:
instantiate_kernel_selection(int8_t,
uint32_t,
float,
CagraSampleFilterWithQueryIdOffset<
cuvs::neighbors::filtering::bitmap_filter<uint32_t COMMA int64_t>>);
update file: search_multi_cta_00_generate.py
for type_path, (data_t, idx_t, distance_t) in search_types.items():
path = f"search_multi_cta_{type_path}.cu"
with open(path, "w") as f:
f.write(header)
f.write(
f"instantiate_kernel_selection(\n {data_t}, {idx_t}, {distance_t}, cuvs::neighbors::filtering::none_sample_filter);\n"
)
f.write(
f"instantiate_kernel_selection(\n {data_t}, {idx_t}, {distance_t}, CagraSampleFilterWithQueryIdOffset<cuvs::neighbors::filtering::bitset_filter<uint32_t COMMA int64_t>>);\n"
)
f.write(
f"instantiate_kernel_selection(\n {data_t}, {idx_t}, {distance_t}, CagraSampleFilterWithQueryIdOffset<cuvs::neighbors::filtering::bitmap_filter<uint32_t COMMA int64_t>>);\n"
)
f.write(trailer)
# For pasting into CMakeLists.txt
print(f"src/neighbors/detail/cagra/{path}")
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with search_multi_cta_00_generate.py and inspect how it writes the search_multi_cta_*.cu files. Update the generator to emit the bitmap_filter instantiation alongside the existing filters, then verify that the generated CUDA files contain the requested CagraSampleFilterWithQueryIdOffset specialization.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- search
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 45/100