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Thanks for your working, this is a great implementation. I'm using tsne-cuda on Linux OS with NVIDIA GPU. Running tsnecuda.test() is fine but when I run for my code got
Faiss assertion 'err__ == cudaSuccess' failed in void faiss::gpu::ivfInterleavedScanImpl_32_(faiss::gpu::Tensor<float, 2, true>&, faiss::gpu::Tensor<int, 2, true>&, thrust::device_vector<void*>&, thrust::device_vector<void*>&, faiss::gpu::IndicesOptions, thrust::device_vector<int>&, int, faiss::MetricType, bool, faiss::gpu::Tensor<float, 3, true>&, faiss::gpu::GpuScalarQuantizer*, faiss::gpu::Tensor<float, 2, true>&, faiss::gpu::Tensor<long int, 2, true>&, faiss::gpu::GpuResources*) at /home/conda/feedstock_root/build_artifacts/faiss-split_1636459943780/work/faiss/gpu/impl/scan/IVFInterleaved32.cu:13; details: CUDA error 9 invalid configuration argumentHere is how I run:
from tsnecuda import TSNE
tsne_embedding = TSNE(
n_components=2,
perplexity=perplexity,
early_exaggeration=early_exaggeration,
learning_rate=learning_rate,
n_iter=n_iter,
metric=metric,
init='random',
).fit_transform(embedding)and I install tsnecuda by conda command:
conda install tsnecuda -c cannylaband
conda install tsnecuda -c conda-forgebut none of them work.
artemZholus and David-Dou
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