Open AdotaLover opened 1 month ago
window无法运行mclapply的并行计算 system.time({ embeddings.df <- FetchData(seu.ref, vars = paste0("UMAP_", 1:2)) batch.size = 5000 # number of subsampled cells for each SVR model n.models = 20 # number of SVR models trained umap.model <- FitEnsembleSVM(feature.mat = gss.mat, emb.mat = embeddings.df, do.norm = "L2", batch.size = batch.size, n.models = n.models )
}) L2 normalization ... Creating regression tasks: size=5000, n=20 |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s Regression ... 错误于parallel::mclapply(1:n.models, function(j) .train(coord_i, j), : Windows不支持'mc.cores' > 1 Timing stopped at: 0.8 0.06 0.9
ProjectSVR现在不支持在win平台下的并行计算,这种情况设置mc.cores=1即可。
window无法运行mclapply的并行计算 system.time({ embeddings.df <- FetchData(seu.ref, vars = paste0("UMAP_", 1:2)) batch.size = 5000 # number of subsampled cells for each SVR model n.models = 20 # number of SVR models trained umap.model <- FitEnsembleSVM(feature.mat = gss.mat, emb.mat = embeddings.df, do.norm = "L2", batch.size = batch.size, n.models = n.models )
}) L2 normalization ... Creating regression tasks: size=5000, n=20 |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s
Regression ... 错误于parallel::mclapply(1:n.models, function(j) .train(coord_i, j), : Windows不支持'mc.cores' > 1 Timing stopped at: 0.8 0.06 0.9