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when I analysis 1 million cells collected by myself using multigpu, step of dask_sparse_arr.compute_chunk_sizes() is error. Error information is below:
cuml/linear_model/linear_regression.pyx in cuml.linear_model.linear_regression.LinearRegression.fit() RuntimeError: exception occured! file=_deps/raft-src/cpp/include/raft/linalg/eig.cuh line=144: eig.cuh: eigensolver couldn't converge to a solution. This usually occurs when some of the features do not vary enough.
Obtained 64 stack frames
The text was updated successfully, but these errors were encountered:
when I analysis 1 million cells collected by myself using multigpu, step of dask_sparse_arr.compute_chunk_sizes() is error. Error information is below:
cuml/linear_model/linear_regression.pyx in cuml.linear_model.linear_regression.LinearRegression.fit() RuntimeError: exception occured! file=_deps/raft-src/cpp/include/raft/linalg/eig.cuh line=144: eig.cuh: eigensolver couldn't converge to a solution. This usually occurs when some of the features do not vary enough. Obtained 64 stack frames
en, when I change HVG(highly variable genes) from 2000 to 4000, the problem did not recur.
when I analysis 1 million cells collected by myself using multigpu, step of dask_sparse_arr.compute_chunk_sizes() is error. Error information is below:
cuml/linear_model/linear_regression.pyx in cuml.linear_model.linear_regression.LinearRegression.fit()
RuntimeError: exception occured! file=_deps/raft-src/cpp/include/raft/linalg/eig.cuh line=144: eig.cuh: eigensolver couldn't converge to a solution. This usually occurs when some of the features do not vary enough.
Obtained 64 stack frames
The text was updated successfully, but these errors were encountered: