Comments (1)
For future reference, this is just a warning when you use very few points in the FAISS library. Because this was designed to be optimal for large numbers of points, when you use smaller sets of points, you are doing more bookkeeping work than is necessary. Nothing is going wrong with the library, it just many not be optimal in terms of performance.
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Related Issues (20)
- 403 Error when downloading wheels HOT 1
- Failed to cudaFree pointer issue & Memory issue HOT 2
- tsnecuda equivalent for M1 chip HOT 1
- Warning gives a moving target number of training points that could not be satisfied HOT 1
- CUBLAS_STATUS_NOT_INITIALIZED
- CUDA error 209 no kernel image is available for execution on the device HOT 6
- Aborted (core dumped) without any other error messages HOT 1
- TSNE(n_components=1)
- Throws an OSError when initializing HOT 4
- CUBLAS_STATUS_INVALID_VALUE
- CUBLAS_STATUS_NOT_INITIALIZED when importing Datashader *before* running tsnecuda HOT 1
- stuck at Initializing cuda handles HOT 3
- Fail with CUDA error 9. HOT 3
- tsne.fit_transform() prematurely ends before function return in a function call
- Gradient problem HOT 1
- ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory HOT 1
- Is there any way to select the GPU ordinal for the tSNE execution? HOT 1
- random_seed does not seem to work HOT 1
- Binary installation for Windows10 not possible HOT 2
- tsnecuda.test() fail
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