System information
- Mac 0S Mojave 10.14.3:
- dotnet --version
2.2.300
- Project references
- Microsoft.ML
- Microsoft.ML.Mkl.Redis
- Microsoft.ML.TimeSeries
Issue
Source code / logs
Unable to load shared library 'MklImports' or one of its dependencies. In order to help diagnose loading problems, consider setting the DYLD_PRINT_LIBRARIES environment variable: dlopen(libMklImports, 1): image not found
at Microsoft.ML.Transforms.TimeSeries.EigenUtils.Dsytrd(Layout matrixLayout, Uplo uplo, Int32 n, Double[] a, Int32 lda, Double[] d, Double[] e, Double[] tau)\n at Microsoft.ML.Transforms.TimeSeries.EigenUtils.MklSymmetricEigenDecomposition(Single[] input, Int32 size, Single[]& eigenValues, Single[]& eigenVectors)\n at Microsoft.ML.Transforms.TimeSeries.TrajectoryMatrix.ComputeSvd(Single[]& singularValues, Single[]& leftSingularvectors)\n at Microsoft.ML.Transforms.TimeSeries.AdaptiveSingularSpectrumSequenceModeler.AdaptiveSingularSpectrumSequenceModelerInternal.TrainCore(Single[] dataArray, Int32 originalSeriesLength)\n at Microsoft.ML.Transforms.TimeSeries.AdaptiveSingularSpectrumSequenceModeler.AdaptiveSingularSpectrumSequenceModelerInternal.Train(RoleMappedData data)\n
System information
2.2.300
Issue
Possible that this is of the same origin as MacOS CI legs throwing DllNotFoundException for MklImports #3694 but in case it is a separate case I have posted this issue.
What did you do?
Followed new forecasting tutorial for ML.Net 1.1
https://github.com/dotnet/machinelearning/blob/master/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/Forecasting.cs
What happened?
Dll not found exception
What did you expect?
Program to run successfully
Source code / logs
Unable to load shared library 'MklImports' or one of its dependencies. In order to help diagnose loading problems, consider setting the DYLD_PRINT_LIBRARIES environment variable: dlopen(libMklImports, 1): image not found
at Microsoft.ML.Transforms.TimeSeries.EigenUtils.Dsytrd(Layout matrixLayout, Uplo uplo, Int32 n, Double[] a, Int32 lda, Double[] d, Double[] e, Double[] tau)\n at Microsoft.ML.Transforms.TimeSeries.EigenUtils.MklSymmetricEigenDecomposition(Single[] input, Int32 size, Single[]& eigenValues, Single[]& eigenVectors)\n at Microsoft.ML.Transforms.TimeSeries.TrajectoryMatrix.ComputeSvd(Single[]& singularValues, Single[]& leftSingularvectors)\n at Microsoft.ML.Transforms.TimeSeries.AdaptiveSingularSpectrumSequenceModeler.AdaptiveSingularSpectrumSequenceModelerInternal.TrainCore(Single[] dataArray, Int32 originalSeriesLength)\n at Microsoft.ML.Transforms.TimeSeries.AdaptiveSingularSpectrumSequenceModeler.AdaptiveSingularSpectrumSequenceModelerInternal.Train(RoleMappedData data)\n