Open Mi-Peng opened 1 year ago
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
tsnecuda.test()
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 argument
Here 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 cannylab
and
conda install tsnecuda -c conda-forge
but none of them work.
same issue
Is the problem being addressed?
I found it may fail on a large dataset
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 gotHere is how I run:
and I install tsnecuda by conda command:
and
but none of them work.