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Update cuVS repository URLs
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CHANGELOG.md

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Dockerfile

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# Container metadata
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LABEL maintainer="RAPIDS cuVS Team"
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LABEL description="RAPIDS cuVS - Vector Search and Clustering on GPU"
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LABEL org.opencontainers.image.source="https://github.com/rapidsai/cuvs"
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LABEL org.opencontainers.image.source="https://github.com/nvidia/cuvs"
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LABEL org.opencontainers.image.usage="docker run --gpus all -it <image>"
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# Environment setup

README.md

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- [Documentation](https://docs.nvidia.com/cuvs): Library documentation.
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- [Build and Install Guide](https://docs.nvidia.com/cuvs/installation): Instructions for installing and building cuVS.
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- [Getting Started Guide](https://docs.nvidia.com/cuvs/getting-started): Guide to getting started with cuVS.
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- [Code Examples](https://github.com/rapidsai/cuvs/tree/HEAD/examples): Self-contained Code Examples.
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- [Code Examples](https://github.com/nvidia/cuvs/tree/HEAD/examples): Self-contained Code Examples.
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- [API Reference Documentation](https://docs.nvidia.com/cuvs/api_reference): API Documentation.
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- [RAPIDS Community](https://rapids.ai/community.html): Get help, contribute, and collaborate.
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- [GitHub repository](https://github.com/rapidsai/cuvs): Download the cuVS source code.
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- [Issue tracker](https://github.com/rapidsai/cuvs/issues): Report issues or request features.
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- [GitHub repository](https://github.com/nvidia/cuvs): Download the cuVS source code.
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- [Issue tracker](https://github.com/nvidia/cuvs/issues): Report issues or request features.
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## What is cuVS?
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auto index = cagra::build(res, index_params, dataset);
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```
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For more code examples of the C++ APIs, including drop-in Cmake project templates, please refer to the [C++ examples](https://github.com/rapidsai/cuvs/tree/HEAD/examples) directory in the codebase.
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For more code examples of the C++ APIs, including drop-in Cmake project templates, please refer to the [C++ examples](https://github.com/nvidia/cuvs/tree/HEAD/examples) directory in the codebase.
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### C API
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cuvsResourcesDestroy(res);
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```
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For more code examples of the C APIs, including drop-in Cmake project templates, please refer to the [C examples](https://github.com/rapidsai/cuvs/tree/main/examples/c)
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For more code examples of the C APIs, including drop-in Cmake project templates, please refer to the [C examples](https://github.com/nvidia/cuvs/tree/main/examples/c)
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### Rust API
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}
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```
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For more code examples of the Rust APIs, including a drop-in project templates, please refer to the [Rust examples](https://github.com/rapidsai/cuvs/tree/main/examples/rust).
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For more code examples of the Rust APIs, including a drop-in project templates, please refer to the [Rust examples](https://github.com/nvidia/cuvs/tree/main/examples/rust).
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## Contributing
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ci/build_java.sh

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# TODO: Remove this argument-handling when build and test workflows are separated,
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# and test_java.sh no longer calls build_java.sh
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# ref: https://github.com/rapidsai/cuvs/issues/868
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# ref: https://github.com/nvidia/cuvs/issues/868
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EXTRA_BUILD_ARGS=()
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if [[ "${1:-}" == "--run-java-tests" ]]; then
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EXTRA_BUILD_ARGS+=("--run-java-tests")

ci/check_c_abi/pyproject.toml

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check-c-abi = "check_c_abi.main:main_cli"
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[project.urls]
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Homepage = "https://github.com/rapidsai/cuvs"
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Homepage = "https://github.com/nvidia/cuvs"
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[tool.setuptools.dynamic]
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version = { file = "VERSION" }

ci/test_java.sh

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export RAPIDS_CUDA_MAJOR
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# TODO: switch to installing pre-built artifacts instead of rebuilding in test jobs
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# ref: https://github.com/rapidsai/cuvs/issues/868
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# ref: https://github.com/nvidia/cuvs/issues/868
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ci/build_java.sh --run-java-tests
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rapids-logger "Test script exiting with value: $EXITCODE"

cpp/bench/ann/src/diskann/diskann_wrapper.h

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}
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}
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// TODO (tarangj): Remaining features are tracked at https://github.com/rapidsai/cuvs/issues/656
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// TODO (tarangj): Remaining features are tracked at https://github.com/nvidia/cuvs/issues/656
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template <typename T>
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class diskann_memory : public algo<T> {
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public:

cpp/include/cuvs/cluster/kmeans.hpp

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* @brief Find clusters with k-means algorithm using batched processing of host data.
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*
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* TODO: Evaluate replacing the extent type with int64_t. Reference issue:
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* https://github.com/rapidsai/cuvs/issues/1961
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* https://github.com/nvidia/cuvs/issues/1961
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*
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* This overload supports out-of-core computation where the dataset resides
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* on the host. Data is processed in GPU-sized batches, streaming from host to device.

cpp/include/cuvs/cluster/spectral.hpp

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* @{
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*/
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// TODO: int64_t nnz support (see https://github.com/rapidsai/cuvs/issues/1484)
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// TODO: int64_t nnz support (see https://github.com/nvidia/cuvs/issues/1484)
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/**
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* @brief Perform spectral clustering on a connectivity graph

cpp/include/cuvs/neighbors/common.hpp

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* @tparam IdxT The index type for source indices
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* @tparam SizeT The size type
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*
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* TODO: Make this struct internal (tracking issue: https://github.com/rapidsai/cuvs/issues/1726)
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* TODO: Make this struct internal (tracking issue: https://github.com/nvidia/cuvs/issues/1726)
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*/
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template <typename ValueT, typename IdxT, typename SizeT = uint32_t>
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struct list_base {

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