vendor/libxgboost.so in xgb-0.2.0 vs vendor/libxgboost.so in xgb-0.2.1

- old
+ new

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lDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_EEEEEE_ZTINSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_EEEEEE_ZTSNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_EEEEEE_ZTINSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_EEEEEE_ZTSNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_EEEEEE_ZTINSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_EEEEEE_ZTSNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_EEEEEE_ZTINSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_EEEEEE_ZTSNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_EEEEEE_ZTINSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_EEEEEE_ZTSN4dmlc12RowBlockIterIjfEE_ZTIN4dmlc12RowBlockIterIjfEE_ZTSN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTSN4dmlc12RowBlockIterImfEE_ZTIN4dmlc12RowBlockIterImfEE_ZTSN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTSN4dmlc12RowBlockIterIjiEE_ZTIN4dmlc12RowBlockIterIjiEE_ZTSN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTSN4dmlc12RowBlockIterImiEE_ZTIN4dmlc12RowBlockIterImiEE_ZTSN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTSN4dmlc12RowBlockIterIjlEE_ZTIN4dmlc12RowBlockIterIjlEE_ZTSN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTSN4dmlc12RowBlockIterImlEE_ZTIN4dmlc12RowBlockIterImlEE_ZTSN4dmlc6ParserImfEE_ZTIN4dmlc6ParserImfEE_ZTSN4dmlc6ParserIjiEE_ZTIN4dmlc6ParserIjiEE_ZTSN4dmlc6ParserImiEE_ZTIN4dmlc6ParserImiEE_ZTSN4dmlc6ParserIjlEE_ZTIN4dmlc6ParserIjlEE_ZTSN4dmlc6ParserImlEE_ZTIN4dmlc6ParserImlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc4data11DiskRowIterIjfEE_ZTIN4dmlc4data11DiskRowIterIjfEE_ZTSN4dmlc4data12BasicRowIterIjfEE_ZTIN4dmlc4data12BasicRowIterIjfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc4data11DiskRowIterImfEE_ZTIN4dmlc4data11DiskRowIterImfEE_ZTSN4dmlc4data12BasicRowIterImfEE_ZTIN4dmlc4data12BasicRowIterImfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc4data11DiskRowIterIjiEE_ZTIN4dmlc4data11DiskRowIterIjiEE_ZTSN4dmlc4data12BasicRowIterIjiEE_ZTIN4dmlc4data12BasicRowIterIjiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc4data11DiskRowIterImiEE_ZTIN4dmlc4data11DiskRowIterImiEE_ZTSN4dmlc4data12BasicRowIterImiEE_ZTIN4dmlc4data12BasicRowIterImiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc4data11DiskRowIterIjlEE_ZTIN4dmlc4data11DiskRowIterIjlEE_ZTSN4dmlc4data12BasicRowIterIjlEE_ZTIN4dmlc4data12BasicRowIterIjlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc4data11DiskRowIterImlEE_ZTIN4dmlc4data11DiskRowIterImlEE_ZTSN4dmlc4data12BasicRowIterImlEE_ZTIN4dmlc4data12BasicRowIterImlEE_ZTSN4dmlc4data10ParserImplIjfEE_ZTIN4dmlc4data10ParserImplIjfEE_ZTSN4dmlc4data14TextParserBaseIjfEE_ZTIN4dmlc4data14TextParserBaseIjfEE_ZTSN4dmlc4data12LibSVMParserIjfEE_ZTIN4dmlc4data12LibSVMParserIjfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIter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SaIS5_EE_ZTVSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTVNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZN4dmlc4data14TextParserBaseIjfE9ParseNextEPSt6vectorINS0_17RowBlockContainerIjfEESaIS5_EE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEE_ZTSNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZTINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTISt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EE_ZTSN4dmlc12RowBlockIterIjfEE_ZTIN4dmlc12RowBlockIterIjfEE_ZTSN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImfEEEE_ZTSN4dmlc12RowBlockIterImfEE_ZTIN4dmlc12RowBlockIterImfEE_ZTSN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjiEEEE_ZTSN4dmlc12RowBlockIterIjiEE_ZTIN4dmlc12RowBlockIterIjiEE_ZTSN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImiEEEE_ZTSN4dmlc12RowBlockIterImiEE_ZTIN4dmlc12RowBlockIterImiEE_ZTSN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockIjlEEEE_ZTSN4dmlc12RowBlockIterIjlEE_ZTIN4dmlc12RowBlockIterIjlEE_ZTSN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTIN4dmlc8DataIterINS_8RowBlockImlEEEE_ZTSN4dmlc12RowBlockIterImlEE_ZTIN4dmlc12RowBlockIterImlEE_ZTSN4dmlc6ParserImfEE_ZTIN4dmlc6ParserImfEE_ZTSN4dmlc6ParserIjiEE_ZTIN4dmlc6ParserIjiEE_ZTSN4dmlc6ParserImiEE_ZTIN4dmlc6ParserImiEE_ZTSN4dmlc6ParserIjlEE_ZTIN4dmlc6ParserIjlEE_ZTSN4dmlc6ParserImlEE_ZTIN4dmlc6ParserImlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEE_ZTSN4dmlc4data11DiskRowIterIjfEE_ZTIN4dmlc4data11DiskRowIterIjfEE_ZTSN4dmlc4data12BasicRowIterIjfEE_ZTIN4dmlc4data12BasicRowIterIjfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEE_ZTSN4dmlc4data11DiskRowIterImfEE_ZTIN4dmlc4data11DiskRowIterImfEE_ZTSN4dmlc4data12BasicRowIterImfEE_ZTIN4dmlc4data12BasicRowIterImfEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEE_ZTSN4dmlc4data11DiskRowIterIjiEE_ZTIN4dmlc4data11DiskRowIterIjiEE_ZTSN4dmlc4data12BasicRowIterIjiEE_ZTIN4dmlc4data12BasicRowIterIjiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEE_ZTSN4dmlc4data11DiskRowIterImiEE_ZTIN4dmlc4data11DiskRowIterImiEE_ZTSN4dmlc4data12BasicRowIterImiEE_ZTIN4dmlc4data12BasicRowIterImiEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEE_ZTSN4dmlc4data11DiskRowIterIjlEE_ZTIN4dmlc4data11DiskRowIterIjlEE_ZTSN4dmlc4data12BasicRowIterIjlEE_ZTIN4dmlc4data12BasicRowIterIjlEE_ZTSN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTIN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEE_ZTSN4dmlc4data11DiskRowIterImlEE_ZTIN4dmlc4data11DiskRowIterImlEE_ZTSN4dmlc4data12BasicRowIterImlEE_ZTIN4dmlc4data12BasicRowIterImlEE_ZTSN4dmlc4data10ParserImplIjfEE_ZTIN4dmlc4data10ParserImplIjfEE_ZTSN4dmlc4data14TextParserBaseIjfEE_ZTIN4dmlc4data14TextParserBaseIjfEE_ZTSN4dmlc4data12LibSVMParserIjfEE_ZTIN4dmlc4data12LibSVMParserIjfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserIjfEE_ZTIN4dmlc4data14ThreadedParserIjfEE_ZTSN4dmlc4data10ParserImplImfEE_ZTIN4dmlc4data10ParserImplImfEE_ZTSN4dmlc4data14TextParserBaseImfEE_ZTIN4dmlc4data14TextParserBaseImfEE_ZTSN4dmlc4data12LibSVMParserImfEE_ZTIN4dmlc4data12LibSVMParserImfEE_ZTSN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTIN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEE_ZTSN4dmlc4data14ThreadedParserImfEE_ZTIN4dmlc4data14ThreadedParserImfEE_ZTSN4dmlc4data11LibFMParserIjfEE_ZTIN4dmlc4data11LibFMParserIjfEE_ZTSN4dmlc4data11LibFMParserImfEE_ZTIN4dmlc4data11LibFMParserImfEE_ZTSN4dmlc4data9CSVParserIjfEE_ZTIN4dmlc4data9CSVParserIjfEE_ZTSN4dmlc4data9CSVParserImfEE_ZTIN4dmlc4data9CSVParserImfEE_ZTSN4dmlc4data10ParserImplIjiEE_ZTIN4dmlc4data10ParserImplIjiEE_ZTSN4dmlc4data14TextParserBaseIjiEE_ZTIN4dmlc4data14TextParserBaseIjiEE_ZTSN4dmlc4data9CSVParserIjiEE_ZTIN4dmlc4data9CSVParserIjiEE_ZTSN4dmlc4data10ParserImplImiEE_ZTIN4dmlc4data10ParserImplImiEE_ZTSN4dmlc4data14TextParserBaseImiEE_ZTIN4dmlc4data14TextParserBaseImiEE_ZTSN4dmlc4data9CSVParserImiEE_ZTIN4dmlc4data9CSVParserImiEE_ZTSN4dmlc4data10ParserImplIjlEE_ZTIN4dmlc4data10ParserImplIjlEE_ZTSN4dmlc4data14TextParserBaseIjlEE_ZTIN4dmlc4data14TextParserBaseIjlEE_ZTSN4dmlc4data9CSVParserIjlEE_ZTIN4dmlc4data9CSVParserIjlEE_ZTSN4dmlc4data10ParserImplImlEE_ZTIN4dmlc4data10ParserImplImlEE_ZTSN4dmlc4data14TextParserBaseImlEE_ZTIN4dmlc4data14TextParserBaseImlEE_ZTSN4dmlc4data9CSVParserImlEE_ZTIN4dmlc4data9CSVParserImlEE_ZTSZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE__ZTSZN4dmlc4data14Threaded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I)LIL)M)I9H LA?HLIIOII?I:L\$L?L)HHL$HL$IyLI@M[LAH)Ll$ LM)M~JEFAADIEJADHM,$I H IIuHD$ HP?HHHIH?H:HHHփ?H)yH@HH9jLFEAL9LfILHMcM)MII VHLNI)LL$ HMZ~D$ flH4M1IHH)FL9rLHI9I4t7HNLH9t+HNLNH9tHNLNH9tHN LNH9tLN *IL!M?uHI9He1Ƀu I9IIEtL M?uHI9OHM1fDHD$(Ht(H'IEAEIEAEH\$HD$AEM}EeHI]IE HX[]A\A]A^A_f.HH!IIEIEIA?IHA?fDEusI1A9u L9t!@LHHI!0?t79uL9uH|$HD$HGD$GHX[]A\A]A^A_I1H1AH9u9tMIL ?tH9tMIL ?uH1HID|$ HHt$IH)I9I9HICHH9H?HHHD$H(HT$IuHD$IHt$(I)H9tLHEHD$ALMLD$0DLL$1ADIt7H8LHHIHI H!I1IEӃ?HuIH1IuɉIIT$?MIIHL<LH?H:IA?I)yI@II9'D\$ HPAI9LPMHHMcM)ЃLHI zH`LXH)L\$8HLO~D$8flH<M1IfDHH)GL9rLHI9I<t7HwLI9t+HwL_I9tHwL_I9tHw L_I9tL_ $HH!8?uHH9tLH 1fDH9ut(HHEtH 8?uHH9H1̀|$ L1ɾI9uA9t,HHHH!?t I9tH1IEAUH+D$H4H+t$0H!f.A?tJAHIDHHIIHH HH!LEHE?IuH1A?uIE1@L1ɾA9u I9XHHH ?tA9tHHH ?uH1@HD$H@HD$HD$HHGEHAu8fH9u9MILHH!?t=H9tH19u H9M‰IL ?t݃9t@H1HHD$HfM7|$ u:@I9u A92HHHH!?tAI9tH1A9u I9HHH ?tރA9t@H1LI11 HH=0f.1@1 HHbasic_string::_M_construct null not validDMatrix/Booster has not been intialized or has already been disposed.XGBoost distributed mode detected, There are NAN in the matrix, however, you did not set missing=NANmat.info.num_row_ == offset_vec.size() - 1src.info.group_ptr_.size() == 0Uslice does not support group structure/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/span.hCheck failed: _ptr || _count == 0static_cast<xgboost::bst_ulong>(ridx) < batch.Size()Stack trace: -_Z +basic_string::basic_string [bt] () %s: __pos (which is %zu) > this->size() (which is %zu)%02d:%02d:%02d] /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/c_api/c_api.ccCheck failed: at_first_cannot reset NativeDataIterAssertError:%s -read can not have position excceed buffer lengthwrite position exceed fixed buffer sizefloat32float64bool8int32int8int16int64Unknown data table type.vector::_M_default_appendUnknown float field name root_indexUnknown uint field name textwill split data among workersautovector::reservemat.info.num_col_ <= num_colnum_col= vs Check failed: nan_missingmat.info.num_row_ <= num_rowCheck failed: !badnan[i]Check failed: iter->Next()Check failed: _count >= 0H vs. vector::_M_fill_insert/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/././feature_map.hfid == static_cast<int>(names_.size())unknown feature type, use i for indicator and q for quantityCheck failed: floatvector::_M_range_insertSAVED_PARAM_basic_string::substrCheck failed: learner_->GetAttr(attr_name, &saved_param_value)St11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN5rabit5utils19MemoryFixSizeBufferEN5rabit5utils18MemoryBufferStreamEN4dmlc8DataIterIN7xgboost10SparsePageEEEN7xgboost10DataSourceEN4dmlc8DataIterINS_8RowBlockIjfEEEEN4dmlc6ParserIjfEEN7xgboost14NativeDataIterESt15_Sp_counted_ptrIPN7xgboost7DMatrixELN9__gnu_cxx12_Lock_policyE2EE /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/common/hist_util.cc/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/common/././quantile.hfi.Read(&this->size, sizeof(this->size)) == sizeof(this->size)fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry)Check failed: index_ < span_->size()Check failed: 0 <= index_ && index_ != span_->size()nthread == omp_get_num_threads()summary_array.size() == in_sketchs->size()cut.size() <= std::numeric_limits<uint32_t>::max()Check failed: nlevel <= limit_size * epsRow does not lie in any group! -Check failed: cbegin != cendHistCutMatrixibegin + inst.size() == iendcut_size > row_ptr.back()Initinvalid init parametercut.cut.size() > 0U/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptr/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/common/./span.h check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < nquantile: too many large chunk======== Monitor: ========Timer for calls @ /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/common/././timer.h did not get stopped properly.mingap=, maxgap=, wgap=bug in combineCheck failed: size <= sa.size + sb.sizeN7xgboost6common13HistCutMatrixEo;o: A?eACh㈵>?0CSize() == other.size()/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/common/host_device_vector.ccSize() == other.Size()value for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter of is not presented/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/data.ccCheck failed: batch.index != nullptroffset_vec.back() == data.Size()self_offset.size() == other_offset.size()vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.Check failed: fi->Read(&version, sizeof(version)) == sizeof(version)Check failed: version >= 1 && version <= kVersionMetaInfo: unsupported file versionCheck failed: fi->Read(&num_row_, sizeof(num_row_)) == sizeof(num_row_)Check failed: fi->Read(&num_col_, sizeof(num_col_)) == sizeof(num_col_)Check failed: fi->Read(&num_nonzero_, sizeof(num_nonzero_)) == sizeof(num_nonzero_)Check failed: fi->Read(&labels_.HostVector())Check failed: fi->Read(&group_ptr_)Check failed: fi->Read(&qids_)Check failed: fi->Read(&weights_.HostVector())Check failed: fi->Read(&root_index_)Check failed: fi->Read(&base_margin_.HostVector()), required optional, default=.row.page.fmt-Unknown format type self_data.size(): other_data.size(): beg < data.size()ptr < offset.size().rXGBOOST_TEST_NPARTLoad part of data parts matrix with entries loaded from basic_string::append.group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from Unknown data typeMetaInfo: invalid versionMetaInfo: invalid formatInvalid Parameter format for expect but value='Invalid Input: '', valid values are: /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/../common/io.hNot implementedmap::at/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/././parameter.henum_back_map_.count(value) != 0UValue not found in enum declaredN4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN7xgboost7DMatrixEN7xgboost6common16PeekableInStreamEOOOOAAGGGG?/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_csr_source.ccCheck failed: fi->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)invalid format, magic number mismatchCheck failed: info.qids_.empty() || info.qids_.size() == info.num_row_invalid input file formattmagic == kMagicN7xgboost4data15SimpleCSRSourceE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: page_ != nullptrCheck failed: _idx >= 0 && _idx < size()N7xgboost17BatchIteratorImplEN7xgboost4data13SimpleDMatrixEN7xgboost4data23SimpleBatchIteratorImplE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: source_ != nullptrN7xgboost4data17SparsePageDMatrixEN7xgboost4data23SparseBatchIteratorImplE.sorted.col.page/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_raw_format.ccCheck failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()fid + 1 < disk_offset_.size()Invalid SparsePage filedisk_offset_[fid] > curr_offsetfi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry)page->offset.Size() != 0Ufi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry)Raw binary data format.N7xgboost4data16SparsePageFormatEN7xgboost4data19SparsePageRawFormatE*N7xgboost4dataUlvE_E/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_source.ccSparsePageSource: Finished writing to SparsePageSource::CreateRowPage Finished writing to finfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)Check failed: fi->Read(&format)/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?cache_shards.size() != 0U.sorted.col.pageUnknown page type: Writing to MB/s, writtenWriting Invalid page formatCheck failed: producer_sig_ == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_ == kDestroyCheck failed: cell != __null || produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_ != kDestroyCheck failed: !producer_sig_processed_N7xgboost4data16SparsePageSourceEN4dmlc12ThreadedIterIN7xgboost10SparsePageEEE*ZN7xgboost4data16SparsePageSourceC4ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES9_EUlPPNS_10SparsePageEE_*ZN7xgboost4data16SparsePageSourceC4ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES9_EUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterIN7xgboost10SparsePageEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_EEEEEE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/data/sparse_page_writer.ccname_shards.size() == format_shards.size()SparsePage::Writer Finished writing to Check failed: *out_page == nullptrCheck failed: qrecycle_.Pop(out_page)*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7xgboost4data16SparsePageWriterC4ERKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISC_EESG_mEUlvE_EEEEEESt15_Sp_counted_ptrIPN7xgboost10SparsePageELN9__gnu_cxx12_Lock_policyE2EELinear booster, implement generalized linear model./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gblinear.ccgblinear does not support prediction of leaf index/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/parameter.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./strtonum.h*p == ')'Invalid NAN literalOut of range valuepos <= value.length()Out of range value for , value='No conversion could be performedSome trailing characters could not be parsed: '/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./../../src/common/span.hntree_limit == 0UGBLinear::PredictContribution: ntrees is only valid for gbtree predictor/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./data.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/gbm/gblinear_model.hfi->Read(&param, sizeof(param)) == sizeof(param)/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/../common/timer.hjson { 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HI@HH@MR=HM<IO@H~}IF@HHD$0EHAu3H9u9MILHH!?t7H9tH1H9u9MÉIL ?t݃H9tH111|$HAu5H9u +9D$FMILHH! +?t:H9tH19D$u H9MÉIL ?tۃ9D$tH1H= *3f.1<@1;HHbasic_string::_M_construct null not valid/home/runner/work/ml-builds/ml-builds/xgboost/src/c_api/c_api.cc%s: __pos (which is %zu) > this->size() (which is %zu)read can not have position excceed buffer lengthwrite position exceed fixed buffer sizeDMatrix/Booster has not been intialized or has already been disposed.XGBoost distributed mode detected, There are NAN in the matrix, however, you did not set missing=NANmat.info.num_row_ == offset_vec.size() - 1src.info.group_ptr_.size() == 0Uslice does not support group structure/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/../../src/common/span.hCheck failed: _ptr || _count == 0static_cast<xgboost::bst_ulong>(ridx) < batch.Size()Check failed: learner_->GetAttr(attr_name, &saved_param_value)/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/././feature_map.hfid == static_cast<int>(names_.size())unknown feature type, use i for indicator and q for quantity%02d:%02d:%02d] Stack trace: +_Z +basic_string::basic_string [bt] () Check failed: at_first_cannot reset NativeDataIterAssertError:%s +float32float64bool8int32int8int16int64Unknown data table type.vector::_M_default_appendUnknown float field name root_indexUnknown uint field name vs. vector::_M_range_insertwill split data among workersautovector::reserveCheck failed: mat.info.num_col_ <= num_colnum_col= vs Check failed: nan_missingmat.info.num_row_ <= num_rowvector::_M_fill_insertCheck failed: !badnan[i]Check failed: iter->Next()Check failed: _count >= 0SAVED_PARAM_basic_string::substrfloattextXpxSt11_Mutex_baseILN9__gnu_cxx12_Lock_policyE2EESt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EEN4dmlc5ErrorEN4dmlc6StreamEN4dmlc10SeekStreamEN4dmlc7istream5InBufEN4dmlc7istreamEN5rabit5utils19MemoryFixSizeBufferEN5rabit5utils18MemoryBufferStreamEN4dmlc8DataIterIN7xgboost10SparsePageEEEN7xgboost10DataSourceEN4dmlc8DataIterINS_8RowBlockIjfEEEEN4dmlc6ParserIjfEEN7xgboost14NativeDataIterESt15_Sp_counted_ptrIPN7xgboost7DMatrixELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/common/hist_util.cc/home/runner/work/ml-builds/ml-builds/xgboost/src/common/././quantile.hfi.Read(&this->size, sizeof(this->size)) == sizeof(this->size)fi.Read(this->data, this->size * sizeof(Entry)) == this->size * sizeof(Entry)/home/runner/work/ml-builds/ml-builds/xgboost/src/common/./span.hquantile: too many large chunk/home/runner/work/ml-builds/ml-builds/xgboost/src/common/././timer.h did not get stopped properly.Check failed: size <= sa.size + sb.sizeCheck failed: index_ < span_->size()nthread == omp_get_num_threads()Check failed: 0 <= index_ && index_ != span_->size()summary_array.size() == in_sketchs->size()cut.size() <= std::numeric_limits<uint32_t>::max()Check failed: nlevel <= limit_size * eps/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/data.hCheck failed: impl_ != nullptrRow does not lie in any group! +Check failed: cbegin != cend check quantile stats, nbig=, n= srcsize=, maxsize=, range=, chunk=] rmin=, rmax=, wmin=, v=Check failed: nbig < n======== Monitor: ========Timer for calls @ HistCutMatrixmingap=, maxgap=, wgap=bug in combineibegin + inst.size() == iendcut_size > row_ptr.back()Initinvalid init parametercut.cut.size() > 0UN7xgboost6common13HistCutMatrixEo;o: A?eACh㈵>?Size() == other.Size()Size() == other.size()/home/runner/work/ml-builds/ml-builds/xgboost/src/common/host_device_vector.ccvalue for Parameter exceed bound [ should be greater equal to should be smaller equal to Required parameter of is not presented.row.page.fmt-Invalid Parameter format for expect but value=' optional, default=, requiredNot implementedUnknown format type map::atInvalid Input: '', valid values are: self_data.size(): other_data.size(): beg < data.size()ptr < offset.size().rXGBOOST_TEST_NPARTLoad part of data parts matrix with entries loaded from basic_string::append.group groups are loaded from .base_margin base_margin are loaded from .weight weights are loaded from Unknown data typeMetaInfo: invalid versionMetaInfo: invalid format/home/runner/work/ml-builds/ml-builds/xgboost/src/data/data.cc/home/runner/work/ml-builds/ml-builds/xgboost/src/data/../common/io.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././parameter.henum_back_map_.count(value) != 0UValue not found in enum declaredCheck failed: batch.index != nullptroffset_vec.back() == data.Size()self_offset.size() == other_offset.size()vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)cache_file.find('#') == std::string::nposOnly one `#` is allowed in file path for cache file specification.Check failed: fi->Read(&version, sizeof(version)) == sizeof(version)Check failed: version >= 1 && version <= kVersionMetaInfo: unsupported file versionCheck failed: fi->Read(&num_row_, sizeof(num_row_)) == sizeof(num_row_)Check failed: fi->Read(&num_col_, sizeof(num_col_)) == sizeof(num_col_)Check failed: fi->Read(&num_nonzero_, sizeof(num_nonzero_)) == sizeof(num_nonzero_)Check failed: fi->Read(&labels_.HostVector())Check failed: fi->Read(&group_ptr_)Check failed: fi->Read(&qids_)Check failed: fi->Read(&weights_.HostVector())Check failed: fi->Read(&root_index_)Check failed: fi->Read(&base_margin_.HostVector())N4dmlc10ParamErrorEN4dmlc9parameter16FieldAccessEntryEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIiEEiEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIiEEiEEN4dmlc9parameter10FieldEntryIiEEN7xgboost7DMatrixEN7xgboost6common16PeekableInStreamEOOOOAAGGGG?invalid input file formattmagic == kMagic/home/runner/work/ml-builds/ml-builds/xgboost/src/data/simple_csr_source.ccCheck failed: fi->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)invalid format, magic number mismatchCheck failed: info.qids_.empty() || info.qids_.size() == info.num_row_N7xgboost4data15SimpleCSRSourceE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/simple_dmatrix.ccCheck failed: page_ != nullptrCheck failed: _idx >= 0 && _idx < size()N7xgboost17BatchIteratorImplEN7xgboost4data13SimpleDMatrixEN7xgboost4data23SimpleBatchIteratorImplE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_dmatrix.ccCheck failed: source_ != nullptrN7xgboost4data17SparsePageDMatrixEN7xgboost4data23SparseBatchIteratorImplE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_raw_format.ccCheck failed: page.offset.Size() != 0 && offset_vec[0] == 0offset_vec.back() == page.data.Size()disk_offset_[fid] > curr_offsetfi->Read(dmlc::BeginPtr(data_vec) + offset_vec[i], size_to_read * sizeof(Entry)) == size_to_read * sizeof(Entry)fi->Read(dmlc::BeginPtr(data_vec), (page->data).Size() * sizeof(Entry)) == (page->data).Size() * sizeof(Entry)fid + 1 < disk_offset_.size()Invalid SparsePage filepage->offset.Size() != 0URaw binary data format.N7xgboost4data16SparsePageFormatEN7xgboost4data19SparsePageRawFormatE*N7xgboost4dataUlvE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_source.cc/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/threadediter.hCheck failed: out_data_ != NULLCalling Value at beginning or end?Check failed: producer_sig_ == kProduceMake sure you call BeforeFirst not inconcurrent with Next!Check failed: produce_end_.load(std::memory_order_acquire)finfo->Read(&tmagic, sizeof(tmagic)) == sizeof(tmagic)Check failed: fi->Read(&format)SparsePageSource: Finished writing to SparsePageSource::CreateRowPage Finished writing to Check failed: producer_sig_ == kDestroyCheck failed: cell != __null || produce_end_.load(std::memory_order_acquire)Check failed: producer_sig_ != kDestroyCheck failed: !producer_sig_processed_cache_shards.size() != 0UInvalid page format.sorted.col.pageUnknown page type: Writing to MB/s, writtenWriting NSt6thread10_Impl_baseEN7xgboost4data16SparsePageSourceEN4dmlc12ThreadedIterIN7xgboost10SparsePageEEE*ZN7xgboost4data16SparsePageSourceC4ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES9_EUlPPNS_10SparsePageEE_*ZN7xgboost4data16SparsePageSourceC4ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES9_EUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost10SparsePageEE4InitESt8functionIFbPPS5_EES7_IFvvEEEUlvE_vEEEESt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterIN7xgboost10SparsePageEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEESaISI_ELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/data/sparse_page_writer.ccname_shards.size() == format_shards.size()Check failed: *out_page == nullptrCheck failed: qrecycle_.Pop(out_page)SparsePage::Writer Finished writing to *NSt6thread5_ImplISt12_Bind_simpleIFZN7xgboost4data16SparsePageWriterC4ERKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISB_EESF_mEUlvE_vEEEE*St23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN7xgboost4data16SparsePageWriterC4ERKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaISC_EESG_mEUlvE_vEEEESaISK_ELN9__gnu_cxx12_Lock_policyE2EESt15_Sp_counted_ptrIPN7xgboost10SparsePageELN9__gnu_cxx12_Lock_policyE2EE/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gblinear.ccgblinear does not support prediction of leaf index/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/parameter.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./strtonum.hNo conversion could be performedSome trailing characters could not be parsed: '/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/./../../src/common/span.h/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/../../src/gbm/gblinear_model.hfi->Read(&param, sizeof(param)) == sizeof(param)GBLinear::PredictContribution: ntrees is only valid for gbtree predictor/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/./data.h/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/../common/timer.h has already been registered in Number of features used in classification.Number of output groups in the setting.Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number.GBLinear::Predict ntrees is only valid for gbtree predictorLinear booster, implement generalized linear model.*p == ')'Invalid NAN literalpos <= value.length()Out of range value for , value='Out of range valuentree_limit == 0Ujson { "bias": [ ], "weight": [ ] }bias: weight: -key has already been registered in num_featureint (non-negative)num_output_groupNumber of features used in classification.Number of output groups in the setting.GBLinearModelParamGBLinearTrainParamgblinearupdatershotguntolerancemax_row_perbatchlong (non-negative)Maximum rows per batch.Update algorithm for linear model. One of shotgun/coord_descentStop if largest weight update is smaller than this number.PredictBatchInternalDoBoostPredictBatchGBLinear::Predict ntrees is only valid for gbtree predictorGBLinearN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN7xgboost15GradientBoosterEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIjEEjEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIjEEjEEN4dmlc9parameter10FieldEntryIjEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryImEEmEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryImEEmEEN4dmlc9parameter10FieldEntryImEEN7xgboost3gbm8GBLinearE*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE_Eŝt LZSgY@v?Unknown gbm type /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbm.ccdistcolTree booster, gradient boosted trees.false/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/gbm/gbtree_model.hparam.num_trees == static_cast<int>(trees.size())/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/tree_model.hparam.num_nodes == static_cast<int>(nodes_.size())param.num_nodes == static_cast<int>(stats_.size())param.num_nodes != 0GBTreeModelParamGBTreeTrainParamDartTrainParamgbtreedartTree booster, dart.fi->Read(&param, sizeof(TreeParam)) == sizeof(TreeParam)fi->Read(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size()) == sizeof(Node) * nodes_.size()fi->Read(dmlc::BeginPtr(stats_), sizeof(RTreeNodeStat) * stats_.size()) == sizeof(RTreeNodeStat) * stats_.size()static_cast<int>(deleted_nodes_.size()) == param.num_deleted/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/gbm/gbtree.ccdrop trees, weight = fi->Read(dmlc::BeginPtr(tree_info), sizeof(int) * param.num_trees) == sizeof(int) * param.num_treesGBTree: invalid model fileTree updater sequence.size_leaf_vectorNumber of output groups to be predicted, used for multi-class classification.Number of features used for training and prediction.Reserved option for vector tree. has not been registered in Alias Enum exisit!) -Enums: ), num_parallel_treeupdater_seqgrow_colmaker,pruneprocess_typedefaultupdatecpu_predictorPredictor algorithm typeNumber of parallel trees constructed during each iteration. This option is used to support boosted random forest.Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model.sample_typeuniformweightednormalize_typeforestrate_dropone_dropbooleanskip_droplearning_rateetaDifferent types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.Learning rate(step size) of update.GBTreemodel_.trees.size() < model_.trees_to_update.size()BoostNewTreesCommitModelin_gpair->Size() % ngroup == 0Umust have exactly ngroup*nrow gpairsnum_group == model_.param.num_output_groupmodel_.param.size_leaf_vector == 0size_leaf_vector is enforced to 0 so farpreds.size() == p_fmat->Info().num_row_ * num_groupout_preds->size() == nN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE_E*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE0_EA;?/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./parameter.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/./common/io.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/learner.ccXGBoost version not compiled with GPU support.Check failed: gbm_ != nullptrPredict must happen after Load or InitModelCheck failed: weights.size() == info.group_ptr_.size() - 1Number of weights should be equal to number of groups in ranking task.weights size: groups size: num rows: /home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/././strtonum.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/./common/timer.hreg:squarederrorLearnerModelParamLearnerTrainParambase_scoreGlobal bias of the model.num_classNumber of features in training data, this parameter will be automatically detected by learner.Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier.seedseed_per_iterationdsplittree_methodapproxgpu_exacttest_flagInternal test flagnthreadNumber of threads to use.disable_default_eval_metricRandom number seed during training.Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode.Data split mode for distributed training.Choice of tree construction method.flag to disable default metric. Set to >0 to disableboostergrow_histmaker,prunegrow_quantile_histmakergrow_gpu,prunegpu_predictorgrow_gpu_histUnknown tree_method () detectedDANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.ȆL܉Check failed: tparam_.dsplit != DataSplitMode::kAutoPrecondition violated; dsplit cannot be 'auto' in distributed modeColumn-wise data split is currently not supported.Tree method is automatically selected to be 'approx' for distributed training.', but only 'approx' and 'hist' is available for distributed training. The `tree_method` parameter is now being changed to 'approx'Distributed training is not available with GPU algoritmsTree method is specified to be 'hist' for distributed training.Tree method is automatically set to 'approx' since external-memory data matrix is used.Tree method was set to be 'exact', but currently we are only able to proceed with approximate algorithm ('approx') because external-memory data matrix is used.External-memory data matrix is not available with GPU algorithmsTree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'.Tree method was set to be @xxBoostOneIterCheck failed: ModelInitialized()Always call InitModel or LoadModel before boost.Check failed: matrix != nullptrnum_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max())Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface?Check failed: obj_ == nullptr && gbm_ == nullptr features or greatermparam_.num_feature != 0Learnerobjectivemulti:softmaxcount:poisson0.7count_poisson_max_delta_stepn_gpusgpu_idUpdateOneIterPredictRawGetGradientAlways call InitModel or LoadModel before updateEvalOneIterbs64header != "bs64"binffp.Read(&header[0], 4) == 4UBase64 format is no longer supported in brick.fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatfi->Read(&len, sizeof(len)) == sizeof(len)fi->Read(&gap, sizeof(gap)) == sizeof(gap)fi->Read(&name_obj_[0], len) == lenCheck failed: fi->Read(&name_gbm_)Parameter 'predictor' will be set to 'cpu_predictor' since XGBoost wasn't compiled with GPU support.N4dmlc12SerializableEN7xgboost7LearnerE*N4dmlc9parameter10FieldEntryIN12_GLOBAL__N_110TreeMethodEEE*N4dmlc9parameter10FieldEntryIN12_GLOBAL__N_113DataSplitModeEEEN7xgboost11LearnerImplE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/linear/linear_updater.ccUnknown linear updater Learning rate ofL2 regularizatioL1 regularizatiofeature_selectorFeature selection or ordering meNumber of devicePrimary device oLinearTrainParamUpdate linear model according to coordinate descent algorithm./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/linear/../common/timer.htop_kThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features.CoordinateParamcoord_descentUpdateFeature/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/linear/coordinate_common.hunknown coordinate selector: SHõN7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearUlvE_E>CoordinateUpdate/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. -Supported options are: {cyclic, shuffle}Update linear model according to shotgun coordinate descent algorithm.N7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearUlvE_EWARNING: DEBUG: INFO: Do not print information during Flag to print out detailed breakdown of runtime.ConsoleLoggerPargamma-nloglikgamma-deviancepoisson-nloglikmaermseNegative loglikelihood for logistic regression.Negative loglikelihood for poisson regression.Residual deviance for gamma regression.Negative log-likelihood for gamma regression.tweedie-nloglik@rho for tweedie regression.tweedie-nloglik@%f/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/metric/elementwise_metric.cusscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metric/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./../../src/common/common.hCheck failed: gpu_id < n_devices_visible +key num_featureint (non-negative)num_output_groupGBLinearModelParamshotgunupdatertoleranceMaximum rows per batch.max_row_perbatchlong (non-negative)GBLinearTrainParamPredictBatchInternalDoBoostPredictBatchGBLineargblinearN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEES8_EEN4dmlc9parameter10FieldEntryINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIfEEfEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIfEEfEEN4dmlc9parameter10FieldEntryIfEEN7xgboost15GradientBoosterEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIjEEjEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIjEEjEEN4dmlc9parameter10FieldEntryIjEEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryImEEmEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryImEEmEEN4dmlc9parameter10FieldEntryImEEN7xgboost3gbm8GBLinearE*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE_EY@v? LUnknown gbm type /home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbm.cc/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/../../src/gbm/gbtree_model.hparam.num_trees == static_cast<int>(trees.size())/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/tree_model.hparam.num_nodes == static_cast<int>(nodes_.size())param.num_nodes == static_cast<int>(stats_.size())fi->Read(&param, sizeof(TreeParam)) == sizeof(TreeParam)fi->Read(dmlc::BeginPtr(nodes_), sizeof(Node) * nodes_.size()) == sizeof(Node) * nodes_.size()fi->Read(dmlc::BeginPtr(stats_), sizeof(RTreeNodeStat) * stats_.size()) == sizeof(RTreeNodeStat) * stats_.size()static_cast<int>(deleted_nodes_.size()) == param.num_deletedfi->Read(dmlc::BeginPtr(tree_info), sizeof(int) * param.num_trees) == sizeof(int) * param.num_trees/home/runner/work/ml-builds/ml-builds/xgboost/src/gbm/gbtree.ccNumber of output groups to be predicted, used for multi-class classification.Number of features used for training and prediction.Reserved option for vector tree.Number of parallel trees constructed during each iteration. This option is used to support boosted random forest.Whether to run the normal boosting process that creates new trees, or to update the trees in an existing model.Different types of sampling algorithm.Different types of normalization algorithm.Fraction of trees to drop during the dropout.Whether at least one tree should always be dropped during the dropout.Probability of skipping the dropout during a boosting iteration.Learning rate(step size) of update.model_.trees.size() < model_.trees_to_update.size()in_gpair->Size() % ngroup == 0Umust have exactly ngroup*nrow gpairsnum_group == model_.param.num_output_groupmodel_.param.size_leaf_vector == 0size_leaf_vector is enforced to 0 so farpreds.size() == p_fmat->Info().num_row_ * num_groupTree booster, gradient boosted trees.distcolfalseparam.num_nodes != 0GBTree: invalid model filedrop trees, weight = has not been registered in Alias Tree updater sequence.size_leaf_vectorGBTreeModelParam exisit!) +Enums: ), Enum num_parallel_treegrow_colmaker,pruneupdater_sequpdatedefaultprocess_typePredictor algorithm typecpu_predictorGBTreeTrainParamweighteduniformsample_typeforestnormalize_typerate_dropone_dropbooleanskip_droplearning_rateetaDartTrainParamGBTreeBoostNewTreesCommitModelout_preds->size() == ngbtreeTree booster, dart.dartN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIbEEbEEN4dmlc9parameter10FieldEntryIbEEN7xgboost3gbm6GBTreeEN7xgboost3gbm4DartE*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE_E*N7xgboost3gbmUlRKSt6vectorISt10shared_ptrINS_7DMatrixEESaIS4_EEfE0_EA;?/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./parameter.h/home/runner/work/ml-builds/ml-builds/xgboost/src/./common/io.h/home/runner/work/ml-builds/ml-builds/xgboost/src/learner.ccXGBoost version not compiled with GPU support.Predict must happen after Load or InitModelCheck failed: weights.size() == info.group_ptr_.size() - 1Number of weights should be equal to number of groups in ranking task./home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././strtonum.h/home/runner/work/ml-builds/ml-builds/xgboost/src/./common/timer.hNumber of features in training data, this parameter will be automatically detected by learner.Number of class option for multi-class classifier. By default equals 0 and corresponds to binary classifier.Random number seed during training.Seed PRNG determnisticly via iterator number, this option will be switched on automatically on distributed mode.Data split mode for distributed training.Choice of tree construction method.flag to disable default metric. Set to >0 to disableDANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.Tree method is selected to be 'hist', which uses a single updater grow_quantile_histmaker.Check failed: tparam_.dsplit != DataSplitMode::kAutoPrecondition violated; dsplit cannot be 'auto' in distributed modeColumn-wise data split is currently not supported.Tree method is automatically selected to be 'approx' for distributed training.', but only 'approx' and 'hist' is available for distributed training. The `tree_method` parameter is now being changed to 'approx'Distributed training is not available with GPU algoritmsTree method is specified to be 'hist' for distributed training.Tree method is automatically set to 'approx' since external-memory data matrix is used.Tree method was set to be 'exact', but currently we are only able to proceed with approximate algorithm ('approx') because external-memory data matrix is used.External-memory data matrix is not available with GPU algorithmsTree method is automatically selected to be 'approx' for faster speed. To use old behavior (exact greedy algorithm on single machine), set tree_method to 'exact'.Check failed: ModelInitialized()Always call InitModel or LoadModel before boost.Check failed: matrix != nullptrnum_col <= static_cast<uint64_t>(std::numeric_limits<unsigned>::max())Unfortunately, XGBoost does not support data matrices with 0 feature is supplied. Are you using raw Booster interface?Check failed: obj_ == nullptr && gbm_ == nullptrAlways call InitModel or LoadModel before updateBase64 format is no longer supported in brick.fi->Read(&mparam_, sizeof(mparam_)) == sizeof(mparam_)BoostLearner: wrong model formatfi->Read(&len, sizeof(len)) == sizeof(len)fi->Read(&gap, sizeof(gap)) == sizeof(gap)fi->Read(&name_obj_[0], len) == lenCheck failed: fi->Read(&name_gbm_)Parameter 'predictor' will be set to 'cpu_predictor' since XGBoost wasn't compiled with GPU support.Check failed: gbm_ != nullptrweights size: groups size: num rows: reg:squarederrorGlobal bias of the model.base_scorenum_classLearnerModelParamseedseed_per_iterationdsplitgpu_exactapproxtree_methodInternal test flagtest_flagNumber of threads to use.nthreaddisable_default_eval_metricLearnerTrainParamboostergrow_histmaker,prunegrow_quantile_histmakergrow_gpu,prunegpu_predictorgrow_gpu_histUnknown tree_method () detectedTree method was set to be BoostOneIter features or greatermparam_.num_feature != 0Learnerobjectivemulti:softmaxcount:poisson0.7count_poisson_max_delta_stepn_gpusgpu_idUpdateOneIterPredictRawGetGradientEvalOneIterbs64header != "bs64"binffp.Read(&header[0], 4) == 4UƧ2 T@ذ@N4dmlc12SerializableEN7xgboost7LearnerE*N4dmlc9parameter10FieldEntryIN12_GLOBAL__N_110TreeMethodEEE*N4dmlc9parameter10FieldEntryIN12_GLOBAL__N_113DataSplitModeEEEN7xgboost11LearnerImplEUnknown linear updater /home/runner/work/ml-builds/ml-builds/xgboost/src/linear/linear_updater.cctop_kCoordinateParamUpdateFeatureunknown coordinate selector: CoordinateUpdatercoord_descent/home/runner/work/ml-builds/ml-builds/xgboost/src/linear/../common/timer.hThe number of top features to select in 'thrifty' feature_selector. The value of zero means using all the features./home/runner/work/ml-builds/ml-builds/xgboost/src/linear/coordinate_common.hUpdate linear model according to coordinate descent algorithm.KN7xgboost13LinearUpdaterEN7xgboost6linear15FeatureSelectorEN7xgboost6linear21CyclicFeatureSelectorEN7xgboost6linear22ShuffleFeatureSelectorEN7xgboost6linear21RandomFeatureSelectorEN7xgboost6linear21GreedyFeatureSelectorEN7xgboost6linear22ThriftyFeatureSelectorEN7xgboost6linear17CoordinateUpdaterE*N7xgboost6linearUlvE_E>/home/runner/work/ml-builds/ml-builds/xgboost/src/linear/updater_shotgun.ccUnsupported feature selector for shotgun updater. +Supported options are: {cyclic, shuffle}Update linear model according to shotgun coordinate descent algorithm.N7xgboost6linear14ShotgunUpdaterE*N7xgboost6linearUlvE_EWARNING: DEBUG: INFO: gamma-nloglikgamma-deviancepoisson-nloglikmaermsetweedie-nloglik@%fgpu_id >= 0gpu_id must be >= 0.n_gpus >= -1n_gpus must be >= -1., number of visible devices: n_gpus <= n_available_devicesStarting from gpu id: , there are only info.labels_.Size() != 0Ulabel set cannot be emptyRooted mean square error.Mean absolute error.Binary classification error.tweedie-nloglik/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/elementwise_metric.cusscanf(param, "%f", &threshold_) == 1unable to parse the threshold value for the error metricCheck failed: param != nullptrtweedie-nloglik must be in format tweedie-nloglik@rhoCheck failed: rho_ < 2 && rho_ >= 1tweedie variance power must be in interval [1, 2)/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/./../../src/common/common.hCheck failed: gpu_id < n_devices_visible gpu_id should be less than number of visible devices. -gpu_id: available devices, while n_gpus is set to: gpu_id >= 0gpu_id must be >= 0.n_gpus >= -1n_gpus must be >= -1., number of visible devices: n_gpus <= n_available_devicesStarting from gpu id: , there are only Check failed: param != nullptrtweedie-nloglik must be in format tweedie-nloglik@rhoCheck failed: rho_ < 2 && rho_ >= 1tweedie variance power must be in interval [1, 2)info.labels_.Size() != 0Ulabel set cannot be emptypreds.Size() == info.labels_.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationRooted mean square error.Mean absolute error.Binary classification error.tweedie-nloglikN7xgboost6MetricEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E*N7xgboost6metricUlPKcE6_E_p0@$]B]/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/metric/metric.ccUnknown metric function Number of GPUs to use for multi-gpu to use for objective functiomerrormloglossMulticlass classification error.Multiclass negative loglikelihood./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels_.Size() == 0label and prediction size not matchmlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class)MultiClassEvaluation: label must be in [0, num_class),nclass >= 1U num_class= but found in labelN7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_Eauccox-nloglikaucprArea under curve for both classification and rank.Area under PR curve for both classification and rank.Negative log partial likelihood of Cox proportioanl hazards model./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/metric/rank_metric.ccAMS must be in format ams@kams@%u[-]?preAMS metric for higgs.precision@k for rank.ndcg@k for rank.map@k for rank.gptr.size() != 0Ugptr.back() == preds.Size()label size predict size not matchmust specify group when constructing rank fileEvalRanklist: group structure must match number of predictionCheck failed: !distributedbest-ams-ratio=metric AMS do not support distributed evaluationCheck failed: !auc_errorgptr.back() == info.labels_.Size()EvalAuc: group structure must match number of predictionAUC: the dataset only contains pos or neg samplesEvalAucPR: group structure must match number of predictionAUC-PR: the dataset only contains pos or neg samplessum_auc <= static_cast<double>(ngroup)AUC-PR: error in calculationdat[0] <= dat[1]AUC-PR: AUC > 1.0Cox metric does not support distributed evaluationt$d%$$%pH8@Tt|N7xgboost6metric7EvalAMSEN7xgboost6metric7EvalAucEN7xgboost6metric12EvalRankListEN7xgboost6metric13EvalPrecisionEN7xgboost6metric8EvalNDCGEN7xgboost6metric7EvalMAPEN7xgboost6metric7EvalCoxEN7xgboost6metric9EvalAucPRE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E$@@Hinge loss. Expects labels to be in [0,1f]/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/hinge.culabels are not correctly providedpreds.size=, label.size=HingeObjParambinary:hingeN7xgboost11ObjFunctionEN7xgboost3obj8HingeObjE*N7xgboost3objUlvE_ESoftmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/multiclass_obj.cuCheck failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size())SoftmaxMultiClassObj: label size and pred size does not matchSoftmaxMultiClassObj: label must be in [0, num_class)./home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/../../src/common/common.hCheck failed: _offset >= 0 && (_offset < size() || size() == 0)Check failed: (_count == dynamic_extent) || (_count >= 0 && _offset + _count <= size())Check failed: (index_ + n) >= 0 && (index_ + n) <= span_->size()Number of output class in the multi-class classification.Number of GPUs to use for multi-gpu algorithms.gpu to use for objective function evaluationSoftmaxMultiClassParammulti:softprobN7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_EҜ<Objective candidate: Unknown objective function /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/objective.cc/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/objective.Number of pair generated for each instance.Normalize the weight of each list by this value, if equals 0, no effect will happenLambdaRank with NDCG as objective.LambdaRank with MAP as objective./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/rank_obj.ccCheck failed: gptr.size() != 0 && gptr.back() == info.labels_.Size()group structure not consistent with #rowsLambdaRankParamnum_pairsamplefix_list_weightrank:pairwisePairwise rank objective.rank:ndcgrank:mapN7xgboost3obj13LambdaRankObjEN7xgboost3obj15PairwiseRankObjEN7xgboost3obj17LambdaRankObjNDCGEN7xgboost3obj16LambdaRankObjMAPE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/regression_obj.cugpu:reg:linear is now deprecated, use reg:linear instead.gpu:reg:logistic is now deprecated, use reg:logistic instead.gpu:binary:logistic is now deprecated, use binary:logistic instead.gpu:binary:logitraw is now deprecated, use binary:logitraw instead.reg:linear is now deprecated in favor of reg:squarederror.Regression with squared error.Logistic regression for probability regression task.Logistic regression for binary classification task.Logistic regression for classification, output score before logistic transformation.Deprecated. Linear regression (computed on GPU).Deprecated. Logistic regression for probability regression task (computed on GPU).Deprecated. Logistic regression for binary classification task (computed on GPU).Deprecated. Logistic regression for classification, output score before logistic transformation (computed on GPU)Possion regression for count data.Cox regression for censored survival data (negative labels are considered censored).Gamma regression for severity data.Tweedie regression for insurance data.GammaRegressionParamRegLossParamPoissonRegressionParamTweedieRegressionParamgpu:reg:lineargpu:reg:logisticgpu:binary:logisticgpu:binary:logitrawsurvival:coxreg:gammareg:tweedie/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/objective/./regression_loss.hCheck failed: base_score > 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic lossPoissonRegression: label must be nonnegativeGammaRegression: label must be nonnegativeTweedieRegression: label must be nonnegativelabel must be in [0,1] for logistic regressionscale_pos_weightScale the weight of positive examples by this factorMaximum delta step we allow each weight estimation to be. This parameter is required for possion regression.tweedie_variance_powerTweedie variance power. Must be between in range [1, 2).Check failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!N7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_22LogisticClassificationEEEN7xgboost3obj10RegLossObjINS0_11LogisticRawEEEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj15GammaRegressionEN7xgboost3obj17TweedieRegressionE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E*N7xgboost3objUlvE2_E*N7xgboost3objUlvE3_E*N7xgboost3objUlvE4_E*N7xgboost3objUlvE5_E*N7xgboost3objUlvE6_E*N7xgboost3objUlvE7_E*N7xgboost3objUlvE8_E*N7xgboost3objUlvE9_E*N7xgboost3objUlvE10_E*N7xgboost3objUlvE11_Eout_preds->Size() == n * base_score = /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/predictor/cpu_predictor.ccWarning: Ignoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. [number of data points], i.e. Instead, all data points will use model.param.size_leaf_vector == 0Make predictions using CPU.N7xgboost9predictor12CPUPredictorE*N7xgboost9predictorUlvE_EUnknown predictor type /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/predictor/predictor.ccN7xgboost9PredictorE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/split_evaluator.ccConstraint of variable monotonicityUse an elastic net regulariserEnforces that the tree is monotonically increasing/decreasing w.r.t. specified featuresEnforces interaction constraints on tree features Line , around ^`Unknown SplitEvaluator MonotonicConstraintParamsmonotone_constraintsInteractionConstraintParamsElasticNetParamselastic_netmonotonicinteractionElasticNet does not accept an inner SplitEvaluatorMonotonicConstraint must be given an inner evaluator/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/././json.h, JSON array expect ']' or ','. Get 'ch == ','Error at' insteadInteractionConstraint must be given an inner evaluatorCheck failed: !std::isnan(mid)Check failed: nodeid < upper_.size()ch == '[', Expect '{' but get 'interaction_constraintsNumber of total features usedConstraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more informationreg_lambdareg_alphaL2 regularization on leaf weightL1 regularization on leaf weightMaximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraintCheck failed: !is_->fail(), Expect numberN7xgboost4tree14SplitEvaluatorEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost4tree10ElasticNetEN7xgboost4tree19MonotonicConstraintEN7xgboost4tree21InteractionConstraintE*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE_E*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE0_E*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE1_E_K_/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/tree_model.ccthis->node_mean_values_.size() > 0Uunique_path[i].pweight == 0Unique path must have zero weight{ "nodeid": , "leaf": , "cover": :leaf=,cover=, "depth": , "split": ", "yes": , "no": :[] yes=,no=, "split_condition": , "missing": <,missing=unknown fmap type, "split": :[f, "gain": ,gain=, "children": []}TreeParam/home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./feature_map.hFeatureMap feature index exceed boundidx < names_.size()Number of start root of trees.Number of features used in tree construction.Size of leaf vector, reserved for vector treemin_split_lossmax_depthmax_leavesmax_bingrow_policydepthwiselossguidemin_child_weightdefault_directionlearnleftrightsubsamplecolsample_bynodecolsample_bylevelcolsample_bytreeopt_dense_colsketch_epssketch_ratioparallel_optioncache_optrefresh_leafsplit_evaluatorsparse_thresholddoubleenable_feature_groupingmax_conflict_ratemax_search_groupMinimum loss reduction required to make a further partition.Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policyMaximum number of leaves; 0 indicates no limit.if using histogram-based algorithm, maximum number of bins per featureTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)Minimum sum of instance weight(hessian) needed in a child.Default direction choice when encountering a missing valueRow subsample ratio of training instance.Subsample ratio of columns, resample on each node (split).Subsample ratio of columns, resample on each level.Subsample ratio of columns, resample on each tree construction.EXP Param: speed optimization for dense column.EXP Param: Sketch accuracy of approximate algorithm.EXP Param: Sketch accuracy related parameter of approximate algorithm.Size of leaf vectors, reserved for vector treesDifferent types of parallelization algorithm.EXP Param: Cache aware optimization.Whether the refresh updater needs to update leaf values.gpu to use for single gpu algorithmsNumber of GPUs to use for multi-gpu algorithms: -1=use all GPUselastic_net,monotonic,interactionThe criteria to use for ranking splitspercentage threshold for treating a feature as sparseif >0, enable feature grouping to ameliorate work imbalance among worker threadswhen grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary.when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined.N4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEHgY?@חA?Unknown tree updater /home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/tree_updater.cc/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_colmaker.ccGrow tree with parallelization over columns.Distributed column split version of tree maker.ridx < position_.size()ridx exceed bound ridx= pos=grow_colmakerCheck failed: !tree[nid].IsLeaf()inconsistent reduce information : /home/runner/work/ml-test-builds/ml-test-builds/xgboost/include/xgboost/./tree_model.hparam.num_nodes < std::numeric_limits<int>::max()number of nodes in the tree exceed 2^31Check failed: node.IsLeaf()__Cannot find argument '', Possible Arguments: +gpu_id: available devices, while n_gpus is set to: preds.Size() == info.labels_.Size()label and prediction size not match, hint: use merror or mlogloss for multi-class classificationNegative loglikelihood for logistic regression.Negative loglikelihood for poisson regression.Residual deviance for gamma regression.Negative log-likelihood for gamma regression.tweedie-nloglik@rho for tweedie regression.N7xgboost6MetricEN7xgboost6metric13EvalEWiseBaseINS0_11EvalRowRMSEEEEN7xgboost6metric13EvalEWiseBaseINS0_10EvalRowMAEEEEN7xgboost6metric13EvalEWiseBaseINS0_14EvalRowLogLossEEEN7xgboost6metric13EvalEWiseBaseINS0_20EvalPoissonNegLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_17EvalGammaDevianceEEEN7xgboost6metric13EvalEWiseBaseINS0_16EvalGammaNLogLikEEEN7xgboost6metric13EvalEWiseBaseINS0_9EvalErrorEEEN7xgboost6metric13EvalEWiseBaseINS0_18EvalTweedieNLogLikEEE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E*N7xgboost6metricUlPKcE6_E$]_p0@Unknown metric function /home/runner/work/ml-builds/ml-builds/xgboost/src/metric/metric.ccmerrormloglossnclass >= 1U num_class= but found in label/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/multiclass_metric.cuCheck failed: preds.Size() % info.labels_.Size() == 0label and prediction size not matchmlogloss and merror are only used for multi-class classification, use logloss for binary classificationCheck failed: label_error >= 0 && label_error < static_cast<int32_t>(n_class)MultiClassEvaluation: label must be in [0, num_class),Multiclass classification error.Multiclass negative loglikelihood.N7xgboost6metric14EvalMClassBaseINS0_14EvalMatchErrorEEEN7xgboost6metric14EvalMatchErrorEN7xgboost6metric14EvalMClassBaseINS0_16EvalMultiLogLossEEEN7xgboost6metric16EvalMultiLogLossE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E]Bauccox-nloglikaucprAMS must be in format ams@kams@%u[-]?pregptr.size() != 0Ugptr.back() == preds.Size()AMS metric for higgs.precision@k for rank.ndcg@k for rank.map@k for rank.Check failed: !distributedbest-ams-ratio=Check failed: !auc_errorAUC-PR: error in calculationdat[0] <= dat[1]AUC-PR: AUC > 1.0/home/runner/work/ml-builds/ml-builds/xgboost/src/metric/rank_metric.cclabel size predict size not matchmust specify group when constructing rank fileEvalRanklist: group structure must match number of predictionArea under curve for both classification and rank.Area under PR curve for both classification and rank.Negative log partial likelihood of Cox proportioanl hazards model.metric AMS do not support distributed evaluationgptr.back() == info.labels_.Size()EvalAuc: group structure must match number of predictionAUC: the dataset only contains pos or neg samplesEvalAucPR: group structure must match number of predictionAUC-PR: the dataset only contains pos or neg samplessum_auc <= static_cast<double>(ngroup)Cox metric does not support distributed evaluationshThhhhf8pB<;l<L<\<N7xgboost6metric7EvalAMSEN7xgboost6metric7EvalAucEN7xgboost6metric12EvalRankListEN7xgboost6metric13EvalPrecisionEN7xgboost6metric8EvalNDCGEN7xgboost6metric7EvalMAPEN7xgboost6metric7EvalCoxEN7xgboost6metric9EvalAucPRE*N7xgboost6metricUlPKcE_E*N7xgboost6metricUlPKcE0_E*N7xgboost6metricUlPKcE1_E*N7xgboost6metricUlPKcE2_E*N7xgboost6metricUlPKcE3_E*N7xgboost6metricUlPKcE4_E*N7xgboost6metricUlPKcE5_E$@@preds.size=, label.size=HingeObjParambinary:hinge/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/../common/transform.hNot part of device code. WITH_CUDA: /home/runner/work/ml-builds/ml-builds/xgboost/src/objective/hinge.culabels are not correctly providedHinge loss. Expects labels to be in [0,1f]N7xgboost11ObjFunctionEN7xgboost3obj8HingeObjE*N7xgboost3objUlvE_ESoftmaxMultiClassParammulti:softprob/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/multiclass_obj.cuCheck failed: preds.Size() == (static_cast<size_t>(param_.num_class) * info.labels_.Size())SoftmaxMultiClassObj: label size and pred size does not matchSoftmaxMultiClassObj: label must be in [0, num_class)./home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/../../src/common/common.hCheck failed: _offset >= 0 && (_offset < size() || size() == 0)Check failed: (_count == dynamic_extent) || (_count >= 0 && _offset + _count <= size())Check failed: (index_ + n) >= 0 && (index_ + n) <= span_->size()Number of output class in the multi-class classification.Number of GPUs to use for multi-gpu algorithms.gpu to use for objective function evaluationSoftmax for multi-class classification, output class index.Softmax for multi-class classification, output probability distribution.N7xgboost3obj20SoftmaxMultiClassObjE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_EҜ<Objective candidate: Unknown objective function /home/runner/work/ml-builds/ml-builds/xgboost/src/objective/objective.ccLambdaRankParamnum_pairsamplefix_list_weightPairwise rank objective.rank:pairwiserank:ndcgrank:map/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/rank_obj.ccCheck failed: gptr.size() != 0 && gptr.back() == info.labels_.Size()group structure not consistent with #rowsNumber of pair generated for each instance.Normalize the weight of each list by this value, if equals 0, no effect will happenLambdaRank with NDCG as objective.LambdaRank with MAP as objective.N7xgboost3obj13LambdaRankObjEN7xgboost3obj15PairwiseRankObjEN7xgboost3obj17LambdaRankObjNDCGEN7xgboost3obj16LambdaRankObjMAPE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_Escale_pos_weightRegLossParamtweedie_variance_powerTweedieRegressionParamGammaRegressionParamPoissonRegressionParamgpu:reg:lineargpu:reg:logisticgpu:binary:logisticgpu:binary:logitrawsurvival:coxreg:gammareg:tweedie/home/runner/work/ml-builds/ml-builds/xgboost/src/objective/regression_obj.cureg:linear is now deprecated in favor of reg:squarederror.gpu:reg:logistic is now deprecated, use reg:logistic instead.gpu:binary:logistic is now deprecated, use binary:logistic instead.gpu:binary:logitraw is now deprecated, use binary:logitraw instead.gpu:reg:linear is now deprecated, use reg:linear instead./home/runner/work/ml-builds/ml-builds/xgboost/src/objective/./regression_loss.hCheck failed: base_score > 0.0f && base_score < 1.0fbase_score must be in (0,1) for logistic lossPoissonRegression: label must be nonnegativeGammaRegression: label must be nonnegativeTweedieRegression: label must be nonnegativelabel must be in [0,1] for logistic regressionScale the weight of positive examples by this factorTweedie variance power. Must be between in range [1, 2).Maximum delta step we allow each weight estimation to be. This parameter is required for possion regression.Regression with squared error.Logistic regression for probability regression task.Logistic regression for binary classification task.Logistic regression for classification, output score before logistic transformation.Deprecated. Linear regression (computed on GPU).Deprecated. Logistic regression for probability regression task (computed on GPU).Deprecated. Logistic regression for binary classification task (computed on GPU).Deprecated. Logistic regression for classification, output score before logistic transformation (computed on GPU)Possion regression for count data.Cox regression for censored survival data (negative labels are considered censored).Gamma regression for severity data.Tweedie regression for insurance data.Check failed: last_abs_y <= abs_yCoxRegression: labels must be in sorted order, MetaInfo::LabelArgsort failed!N7xgboost3obj10RegLossObjINS0_16LinearSquareLossEEEN7xgboost3obj10RegLossObjINS0_18LogisticRegressionEEEN7xgboost3obj10RegLossObjINS0_22LogisticClassificationEEEN7xgboost3obj10RegLossObjINS0_11LogisticRawEEEN7xgboost3obj17PoissonRegressionEN7xgboost3obj13CoxRegressionEN7xgboost3obj15GammaRegressionEN7xgboost3obj17TweedieRegressionE*N7xgboost3objUlvE_E*N7xgboost3objUlvE0_E*N7xgboost3objUlvE1_E*N7xgboost3objUlvE2_E*N7xgboost3objUlvE3_E*N7xgboost3objUlvE4_E*N7xgboost3objUlvE5_E*N7xgboost3objUlvE6_E*N7xgboost3objUlvE7_E*N7xgboost3objUlvE8_E*N7xgboost3objUlvE9_E*N7xgboost3objUlvE10_E*N7xgboost3objUlvE11_E/home/runner/work/ml-builds/ml-builds/xgboost/src/predictor/cpu_predictor.ccWarning: Ignoring the base margin, since it has incorrect length. The base margin must be an array of length [num_class] * [number of data points], i.e. [number of data points], i.e. Instead, all data points will use model.param.size_leaf_vector == 0out_preds->Size() == n * base_score = Make predictions using CPU.N7xgboost9predictor12CPUPredictorE*N7xgboost9predictorUlvE_EUnknown predictor type /home/runner/work/ml-builds/ml-builds/xgboost/src/predictor/predictor.ccN7xgboost9PredictorE/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/split_evaluator.ccElasticNet does not accept an inner SplitEvaluatorMonotonicConstraint must be given an inner evaluator/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/././json.h, JSON array expect ']' or ','. Get 'InteractionConstraint must be given an inner evaluatorCheck failed: !std::isnan(mid)Check failed: nodeid < upper_.size()Constraint of variable monotonicityConstraints for interaction representing permitted interactions.The constraints must be specified in the form of a nest list,e.g. [[0, 1], [2, 3, 4]], where each inner list is a group ofindices of features that are allowed to interact with each other.See tutorial for more informationL2 regularization on leaf weightL1 regularization on leaf weightMaximum delta step we allow each tree's weight estimate to be. If the value is set to 0, it means there is no constraintUse an elastic net regulariserEnforces that the tree is monotonically increasing/decreasing w.r.t. specified featuresEnforces interaction constraints on tree features Line , around ^`Unknown SplitEvaluator ch == ','Error at' insteadch == '[', Expect '{' but get 'MonotonicConstraintParamsmonotone_constraintsinteraction_constraintsNumber of total features usedInteractionConstraintParamsreg_lambdareg_alphaElasticNetParamselastic_netmonotonicinteractionCheck failed: !is_->fail(), Expect numberN7xgboost4tree14SplitEvaluatorEN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryISt6vectorIiSaIiEEEES5_EEN4dmlc9parameter10FieldEntryISt6vectorIiSaIiEEEEN7xgboost4tree10ElasticNetEN7xgboost4tree19MonotonicConstraintEN7xgboost4tree21InteractionConstraintE*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE_E*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE0_E*N7xgboost4treeUlSt10unique_ptrINS0_14SplitEvaluatorESt14default_deleteIS2_EEE1_E__/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_model.ccthis->node_mean_values_.size() > 0U/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/./feature_map.hFeatureMap feature index exceed boundNumber of start root of trees.Number of features used in tree construction.Size of leaf vector, reserved for vector treeMinimum loss reduction required to make a further partition.Maximum depth of the tree; 0 indicates no limit; a limit is required for depthwise policyMaximum number of leaves; 0 indicates no limit.if using histogram-based algorithm, maximum number of bins per featureTree growing policy. 0: favor splitting at nodes closest to the node, i.e. grow depth-wise. 1: favor splitting at nodes with highest loss change. (cf. LightGBM)Minimum sum of instance weight(hessian) needed in a child.Default direction choice when encountering a missing valueRow subsample ratio of training instance.Subsample ratio of columns, resample on each node (split).Subsample ratio of columns, resample on each level.Subsample ratio of columns, resample on each tree construction.EXP Param: speed optimization for dense column.EXP Param: Sketch accuracy of approximate algorithm.EXP Param: Sketch accuracy related parameter of approximate algorithm.Size of leaf vectors, reserved for vector treesDifferent types of parallelization algorithm.EXP Param: Cache aware optimization.Whether the refresh updater needs to update leaf values.gpu to use for single gpu algorithmsNumber of GPUs to use for multi-gpu algorithms: -1=use all GPUsThe criteria to use for ranking splitselastic_net,monotonic,interactionpercentage threshold for treating a feature as sparseif >0, enable feature grouping to ameliorate work imbalance among worker threadswhen grouping features, how many "conflicts" to allow.conflict is when an instance has nonzero values for two or more features.default is 0, meaning features should be strictly complementary.when grouping features, how much effort to expend to prevent singleton groups. We'll try to insert each feature into existing groups before creating a new group for that feature; to save time, only up to (max_search_group) of existing groups will be considered. If set to zero, ALL existing groups will be examined.unique_path[i].pweight == 0Unique path must have zero weightidx < names_.size(){ "nodeid": , "leaf": , "cover": :leaf=,cover=, "depth": , "split": ", "yes": , "no": :[] yes=,no=, "split_condition": , "missing": <,missing=unknown fmap type, "split": :[f, "gain": ,gain=, "children": []}TreeParamdoublemin_split_lossmax_depthmax_leavesmax_binlossguidedepthwisegrow_policymin_child_weightrightleftlearndefault_directionsubsamplecolsample_bynodecolsample_bylevelcolsample_bytreeopt_dense_colsketch_epssketch_ratioparallel_optioncache_optrefresh_leafsplit_evaluatorsparse_thresholdenable_feature_groupingmax_conflict_ratemax_search_groupN4dmlc9parameter14FieldEntryBaseINS0_10FieldEntryIdEEdEEN4dmlc9parameter17FieldEntryNumericINS0_10FieldEntryIdEEdEEN4dmlc9parameter10FieldEntryIdEEHgY?@חA?Unknown tree updater /home/runner/work/ml-builds/ml-builds/xgboost/src/tree/tree_updater.cc/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_colmaker.ccCheck failed: !tree[nid].IsLeaf()inconsistent reduce information/home/runner/work/ml-builds/ml-builds/xgboost/include/xgboost/./tree_model.hparam.num_nodes < std::numeric_limits<int>::max()number of nodes in the tree exceed 2^31/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/random.htree.param.num_nodes == tree.param.num_rootsColMaker: can only grow new treefmat.Info().num_row_ == position_.size()root_index[ridx] < (unsigned)tree.param.num_rootsDistColMaker: only support one tree at a timeGrow tree with parallelization over columns.Distributed column split version of tree maker.ridx < position_.size()ridx exceed bound ridx= pos=Check failed: node.IsLeaf()features.size() > 0trees.size() == 1Uvector::_M_emplace_back_auxgrow_colmakerN7xgboost11TreeUpdaterEN7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerEN7xgboost4tree12DistColMaker7BuilderEN7xgboost4tree12DistColMakerE*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_ESt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIiEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE75/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./updater_basemaker-inl.h/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_histmaker.ccnode2workindex_[nid] == static_cast<int>(wid)/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/././param.hinvalid maximum size max_size=Check failed: tree[nid].IsLeaf()FeatHelper fid exceed query bound /home/runner/work/ml-builds/ml-builds/xgboost/src/tree/../common/quantile.hTreeMaker: can only grow new treeroot_index[i] < (unsigned)tree.param.num_rootsTree constructor that uses approximate histogram construction.Tree constructor that uses approximate global proposal of histogram construction.Tree constructor that uses approximate global of histogram construction.Check failed: param_.max_depth > 0max_depth must be larger than 0Finalize: invalid maximum size, max_size=summary_array_.size() == sketchs_.size()this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1this->wspace_.rptr.back() == this->wspace_.cut.size()ret > 0Usketch->temp.size < max_size, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=fv=, hist.size=hist[]=, hist.last=fid * 2 < fminmax_.size()fid * 2 + 1 < fminmax_.size()istart != hist.sizeroot index exceed settinggrow_local_histmakergrow_global_histmakergrow_histmakersketch->temp.size <= max_size, stemp.size=offset == -2this->qexpand_.size() == 1UN7xgboost4tree9BaseMakerEN7xgboost4tree9HistMakerEN7xgboost4tree11CQHistMakerEN7xgboost4tree23GlobalProposalHistMakerEZN7xgboost4tree11CQHistMaker10CreateHistERKSt6vectorINS_6detail20GradientPairInternalIfEESaIS5_EEPNS_7DMatrixERKS2_IjSaIjEERKNS_7RegTreeEEUlvE_*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_E*N7xgboost4treeUlvE1_Eư>Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf()Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf()/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_prune.ccPruner that prune the tree according to statistics.nid >= param.num_rootstree pruning end, roots, extra nodes, pruned nodes, max_depth=N7xgboost4tree10TreePrunerE*N7xgboost4treeUlvE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_quantile_hist.ccgrow_fast_histmaker is deprecated, use grow_quantile_histmaker instead./home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/hist_util.h/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/row_set.hCheck failed: e.begin != nullptraccess element that is not in the setCheck failed: d_step == +1 || d_step == -1cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max())cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max())/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/timer.hCheck failed: (*p_last_tree_)[nid].IsLeaf()upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max())/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/./../common/random.hColMakerHist: can only grow new treeCheck failed: (param_.max_depth > 0 || param_.max_leaves > 0)max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity.max_depth cannot be 0 (unlimited) when grow_policy is depthwise.elem_of_each_node_.size() == 0U(Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram.Grow tree using quantized histogram.row_ptr_[nid] != kMaxGenerating gmat: secQuantile::Builderrow_ptr_[nid] == kMaxout_preds.size() > 0UInitNewNodeApplySplitSubtractionTrickBuildHistBuildLocalHistogramsSyncHistogramsBuildNodeStatsInitDatainfo.root_index_.size() == 0Umin_nbins_per_feature > 0UEvaluateSplitUpdategrow_fast_histmakerFbN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_EN7xgboost4tree17QuantileHistMaker7BuilderEN7xgboost4tree17QuantileHistMakerEPFbN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_E/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_refresh.ccbatch.Size() < std::numeric_limits<unsigned>::max()Refresher that refreshes the weight and statistics according to data.refreshN7xgboost4tree13TreeRefresherEZN7xgboost4tree13TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKSt6vectorIPNS_7RegTreeESaISC_EEEUlvE_*N7xgboost4treeUlvE_E/home/runner/work/ml-builds/ml-builds/xgboost/src/tree/updater_skmaker.ccqexpand_.size() != 0UApproximate sketching maker.grow_skmakerN7xgboost4tree11SketchMakerE*N7xgboost4treeUlvE_EOSyncher that synchronize the tree in all distributed nodes.syncN7xgboost4tree11TreeSyncherE*N7xgboost4treeUlvE_Ecannot call ParseNext : sign == true.split.partname_cache.size() == 1UInvalid uri argument format for key in arg for value in arg name_args.size() == 1UlibsvmUnknown data type File formatindexing_modeLibSVMParserParamlibfmLibFMParserParamFile format.csvlabel_columndelimiterweight_columnCSVParserParamoffset.back() == index.size()__Cannot find argument '', Possible Arguments: ---------------- -/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/random.hfeatures.size() > 0tree.param.num_nodes == tree.param.num_rootsColMaker: can only grow new treefmat.Info().num_row_ == position_.size()root_index[ridx] < (unsigned)tree.param.num_rootstrees.size() == 1UDistColMaker: only support one tree at a timeN7xgboost11TreeUpdaterEN7xgboost4tree8ColMaker7BuilderEN7xgboost4tree8ColMakerEN7xgboost4tree12DistColMaker7BuilderEN7xgboost4tree12DistColMakerE*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_ESt19_Sp_make_shared_tagSt23_Sp_counted_ptr_inplaceIN7xgboost16HostDeviceVectorIiEESaIS2_ELN9__gnu_cxx12_Lock_policyE2EE75/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_histmaker.cc/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/../common/quantile.hCheck failed: tree[nid].IsLeaf()Tree constructor that uses approximate histogram construction.Tree constructor that uses approximate global proposal of histogram construction.Tree constructor that uses approximate global of histogram construction.grow_local_histmakergrow_global_histmakergrow_histmakernode2workindex_[nid] == static_cast<int>(wid)/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/././param.hret > 0U/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./updater_basemaker-inl.hinvalid maximum size max_size=sketch->temp.size < max_size, stemp.sizeINFO: rmax=, sum_total=, naxt_goal=, size=fv=, hist.size=hist[]=, hist.last=fid * 2 < fminmax_.size()fid * 2 + 1 < fminmax_.size()FeatHelper fid exceed query bound TreeMaker: can only grow new treeroot_index[i] < (unsigned)tree.param.num_rootsroot index exceed settingCheck failed: param_.max_depth > 0max_depth must be larger than 0istart != hist.sizesketch->temp.size <= max_size, stemp.size=Finalize: invalid maximum size, max_size=summary_array_.size() == sketchs_.size()this->wspace_.rptr.size() == (fset.size() + 1) * this->qexpand_.size() + 1offset == -2this->qexpand_.size() == 1Uthis->wspace_.rptr.back() == this->wspace_.cut.size()N7xgboost4tree9BaseMakerEN7xgboost4tree9HistMakerEN7xgboost4tree11CQHistMakerEN7xgboost4tree23GlobalProposalHistMakerEZN7xgboost4tree11CQHistMaker10CreateHistERKSt6vectorINS_6detail20GradientPairInternalIfEESaIS5_EEPNS_7DMatrixERKS2_IjSaIjEERKNS_7RegTreeEEUlvE_*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_E*N7xgboost4treeUlvE1_Eư>nid >= param.num_rootstree pruning end, roots, extra nodes, pruned nodes, max_depth=Check failed: nodes_[nodes_[rid].LeftChild() ].IsLeaf()Check failed: nodes_[nodes_[rid].RightChild()].IsLeaf()/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_prune.ccPruner that prune the tree according to statistics.N7xgboost4tree10TreePrunerE*N7xgboost4treeUlvE_E/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_quantile_hist.ccgrow_fast_histmaker is deprecated, use grow_quantile_histmaker instead.Check failed: d_step == +1 || d_step == -1cut_ptr[fid] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max())cut_ptr[fid + 1] <= static_cast<uint32_t>(std::numeric_limits<int32_t>::max())Check failed: (*p_last_tree_)[nid].IsLeaf()upper_bound < static_cast<uint32_t>(std::numeric_limits<int32_t>::max())ColMakerHist: can only grow new treeCheck failed: (param_.max_depth > 0 || param_.max_leaves > 0)max_depth or max_leaves cannot be both 0 (unlimited); at least one should be a positive quantity.max_depth cannot be 0 (unlimited) when grow_policy is depthwise.elem_of_each_node_.size() == 0U(Deprecated, use grow_quantile_histmaker instead.) Grow tree using quantized histogram.Grow tree using quantized histogram./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./../common/row_set.hCheck failed: e.begin != nullptraccess element that is not in the setrow_ptr_[nid] != kMax/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./../common/hist_util.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./../common/timer.hrow_ptr_[nid] == kMaxGenerating gmat: secQuantile::Builderout_preds.size() > 0UInitNewNodeBuildNodeStatsApplySplitSyncHistogramsBuildLocalHistogramsInitDatainfo.root_index_.size() == 0Umin_nbins_per_feature > 0UEvaluateSplitUpdategrow_fast_histmakerSubtractionTrickBuildHist/home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/./../common/random.hFbN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_EN7xgboost4tree17QuantileHistMaker7BuilderEN7xgboost4tree17QuantileHistMakerEPFbN7xgboost4tree17QuantileHistMaker7Builder11ExpandEntryES3_E*N7xgboost4treeUlvE_E*N7xgboost4treeUlvE0_ERefresher that refreshes the weight and statistics according to data./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_refresh.ccbatch.Size() < std::numeric_limits<unsigned>::max()refreshN7xgboost4tree13TreeRefresherEZN7xgboost4tree13TreeRefresher6UpdateEPNS_16HostDeviceVectorINS_6detail20GradientPairInternalIfEEEEPNS_7DMatrixERKSt6vectorIPNS_7RegTreeESaISC_EEEUlvE_*N7xgboost4treeUlvE_Egrow_skmakerApproximate sketching maker./home/runner/work/ml-test-builds/ml-test-builds/xgboost/src/tree/updater_skmaker.ccqexpand_.size() != 0UN7xgboost4tree11SketchMakerE*N7xgboost4treeUlvE_EOsyncSyncher that synchronize the tree in all distributed nodes.N7xgboost4tree11TreeSyncherE*N7xgboost4treeUlvE_E/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/basic_row_iter.h/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/parser.hcannot call ParseNext/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hCheck failed: base <= 10 && base >= 2sign == true.split.partname_cache.size() == 1UInvalid uri argument format for key in arg for value in arg name_args.size() == 1U/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/uri_spec.honly one `#` is allowed in file path for cachefile specificationCheck failed: std::getline(is, kv.first, '=')Check failed: std::getline(is, kv.second)libsvmUnknown data type /home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data.ccFile formatindexing_modeIf >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.LibSVMParserParamLibFMParserParamCSVParserParamCheck failed: TryLoadCache()failed to build cache file finish reading at libfmIf >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.csvFile format.label_columndelimiterweight_columnColumn index (0-based) that will put into label.Delimiter used in the csv file.Column index that will put into instance weights./home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()Check failed: offset.back() == value.size() || value.size() == 0offset.back() == index.size()/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/./libsvm_parser.hparam_.format == "libsvm"/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/libfm_parser.hparam_.format == "libfm"/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/csv_parser.hCheck failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weightsparam_.format == "csv"batch.field[i] <= std::numeric_limits<IndexType>::max()field exceed numeric bound of current typebatch.index[i] <= std::numeric_limits<IndexType>::max()index exceed numeric bound of current typeCheck failed: fi->Read(&label)Check failed: fi->Read(&weight)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))Bad RowBlock formatCheck failed: fi->Read(&qid)MB read,finish reading at %g MB/sec/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/disk_row_iter.hDelimiter '' is not found in the line. Expected '' as the delimiter to separate fields.Check failed: out->label.size() + 1 == out->offset.size()Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()Check failed: out->field.size() == out->index.size()qid:/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/data/././text_parser.hchunk.size != 0UNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_EEEEEEN4dmlc12RowBlockIterIjfEEN4dmlc8DataIterINS_8RowBlockImfEEEEN4dmlc12RowBlockIterImfEEN4dmlc8DataIterINS_8RowBlockIjiEEEEN4dmlc12RowBlockIterIjiEEN4dmlc8DataIterINS_8RowBlockImiEEEEN4dmlc12RowBlockIterImiEEN4dmlc8DataIterINS_8RowBlockIjlEEEEN4dmlc12RowBlockIterIjlEEN4dmlc8DataIterINS_8RowBlockImlEEEEN4dmlc12RowBlockIterImlEEN4dmlc6ParserImfEEN4dmlc6ParserIjiEEN4dmlc6ParserImiEEN4dmlc6ParserIjlEEN4dmlc6ParserImlEEN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEEN4dmlc4data11DiskRowIterIjfEEN4dmlc4data12BasicRowIterIjfEEN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEEN4dmlc4data11DiskRowIterImfEEN4dmlc4data12BasicRowIterImfEEN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEEN4dmlc4data11DiskRowIterIjiEEN4dmlc4data12BasicRowIterIjiEEN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEEN4dmlc4data11DiskRowIterImiEEN4dmlc4data12BasicRowIterImiEEN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEEN4dmlc4data11DiskRowIterIjlEEN4dmlc4data12BasicRowIterIjlEEN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEEN4dmlc4data11DiskRowIterImlEEN4dmlc4data12BasicRowIterImlEEN4dmlc4data10ParserImplIjfEEN4dmlc4data14TextParserBaseIjfEEN4dmlc4data12LibSVMParserIjfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc4data14ThreadedParserIjfEEN4dmlc4data10ParserImplImfEEN4dmlc4data14TextParserBaseImfEEN4dmlc4data12LibSVMParserImfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc4data14ThreadedParserImfEEN4dmlc4data11LibFMParserIjfEEN4dmlc4data11LibFMParserImfEEN4dmlc4data9CSVParserIjfEEN4dmlc4data9CSVParserImfEEN4dmlc4data10ParserImplIjiEEN4dmlc4data14TextParserBaseIjiEEN4dmlc4data9CSVParserIjiEEN4dmlc4data10ParserImplImiEEN4dmlc4data14TextParserBaseImiEEN4dmlc4data9CSVParserImiEEN4dmlc4data10ParserImplIjlEEN4dmlc4data14TextParserBaseIjlEEN4dmlc4data9CSVParserIjlEEN4dmlc4data10ParserImplImlEEN4dmlc4data14TextParserBaseImlEEN4dmlc4data9CSVParserImlEEZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjfEEE_ZN4dmlc4data11DiskRowIterIjfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImfEEE_ZN4dmlc4data11DiskRowIterImfE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjiEEE_ZN4dmlc4data11DiskRowIterIjiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImiEEE_ZN4dmlc4data11DiskRowIterImiE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerIjlEEE_ZN4dmlc4data11DiskRowIterIjlE12TryLoadCacheEvEUlvE0_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlPPNS0_17RowBlockContainerImlEEE_ZN4dmlc4data11DiskRowIterImlE12TryLoadCacheEvEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerIjfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterISt6vectorINS3_4data17RowBlockContainerImfEESaIS8_EEE4InitESt8functionIFbPPSA_EESC_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImfEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImiEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerIjlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEENSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_4data17RowBlockContainerImlEEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io.ccPlease compile with DMLC_USE_HDFS=1 to use hdfsPlease compile with DMLC_USE_S3=1 to use S3Please compile with DMLC_USE_AZURE=1 to use AzureSingleFileSplit: fail to open invalid input parameter for InputSplit::Createneed to pass index file to use IndexedRecordIOfile://hdfs://viewfs://s3://http://https://azure://unknown filesystem protocol stdinCheck failed: fp_ != NULLCheck failed: part < nsplitindexed_recordiounknown input split type rb/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/single_file_split.hCheck failed: part_index == 0 && num_parts == 1InputSplit do not support writeBeforeFirst is not supported/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/cached_input_split.hResetPartition is not supported in CachedInputSplitCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeCheck failed: this->InitCachedIter()Failed to initialize CachedIterFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_2io14InputSplitBase5ChunkEEEN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEEEN4dmlc2io16CachedInputSplitEN4dmlc2io18ThreadedInputSplitEZN4dmlc2io16CachedInputSplit15InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_PFvvEZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlvE0_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlPPNS2_5ChunkEE_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlvE0_NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN4dmlc12ThreadedIterINS3_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_EEEEEECheck failed: begin != end/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/line_split.ccN4dmlc2io12LineSplitterEinvalid record io formatCheck failed: p >= pbegin + 2Invalid RecordIO FormatCheck failed: cflag == 1U/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0(reinterpret_cast<size_t>(begin) & 3UL) == 0U(reinterpret_cast<size_t>(end) & 3UL) == 0UCheck failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end(reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U(reinterpret_cast<size_t>(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: p[0] == RecordIOWriter::kMagicN4dmlc2io16RecordIOSplitterEexpanded_list.size() == 1ul/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccIndexedRecordIOSplitter does not support multiple index filesN4dmlc2io23IndexedRecordIOSplitterE/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()file offset not calculated correctlyThis could due to compiler version, g++-4.9 is neededCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0Unexpected end of regex when escaping.Unexpected end of regex when reading control code.Unexpected end of regex when ascii character.curr=,begin=,end=,fileptr=,fileoffset=offset[ bad regex files_.size() != 0Ufile do not align by bytesNULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodzeroonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atAFJPSVWleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentjuzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerprintpunctupperxdigitvector::_M_realloc_insertUnexpected escape character.Unexpected end of regex when in an open parenthesis.Invalid special open parenthesis.Unexpected end of character class.Unexpected end of regex when in bracket expression.Unexpected character class open bracket.Unexpected character in brace expression.^$\.*+?()[]{}|.[\*^$.[\()*+?{|^$.[\*^$ +param_.format == "libsvm"param_.format == "libfm"param_.format == "csv"Bad RowBlock formatCheck failed: fi->Read(&qid)Delimiter '' is not found in the line. Expected 'MB read,finish reading at %g MB/secCheck failed: TryLoadCache()failed to build cache file finish reading at qid:chunk.size != 0U/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/parser.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/./././strtonum.hCheck failed: base <= 10 && base >= 2/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/uri_spec.honly one `#` is allowed in file path for cachefile specificationCheck failed: std::getline(is, kv.first, '=')Check failed: std::getline(is, kv.second)/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data.ccIf >0, treat all feature indices as 1-based. If =0, treat all feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.If >0, treat all field and feature indices as 1-based. If =0, treat all field and feature indices as 0-based. If <0, use heuristic to automatically detect mode of indexing. See https://en.wikipedia.org/wiki/Array_data_type#Index_origin for more details on indexing modes.Column index (0-based) that will put into label.Delimiter used in the csv file.Column index that will put into instance weights./home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./row_block.hlabel.size() + 1 == offset.size()Check failed: offset.back() == value.size() || value.size() == 0/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/./libsvm_parser.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/libfm_parser.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/csv_parser.hCheck failed: param_.label_column != param_.weight_column || param_.label_column < 0Must have distinct columns for labels and instance weightsCheck failed: fi->Read(&label)Check failed: fi->Read(&weight)Check failed: fi->Read(&field)Check failed: fi->Read(&index)Check failed: fi->Read(&value)Check failed: fi->Read(&max_field, sizeof(IndexType))Check failed: fi->Read(&max_index, sizeof(IndexType))batch.field[i] <= std::numeric_limits<IndexType>::max()field exceed numeric bound of current typebatch.index[i] <= std::numeric_limits<IndexType>::max()index exceed numeric bound of current type' as the delimiter to separate fields.Check failed: out->label.size() + 1 == out->offset.size()Check failed: out->weight.size() == 0 || out->weight.size() + 1 == out->offset.size()/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/disk_row_iter.h/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/basic_row_iter.hCheck failed: out->field.size() == out->index.size()/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/data/././text_parser.hNSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS3_17RowBlockContainerImlEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS3_17RowBlockContainerIjlEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS3_17RowBlockContainerImiEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS3_17RowBlockContainerIjiEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS3_17RowBlockContainerImfEESaIS8_EEEUlvE_vEEEENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS3_17RowBlockContainerIjfEESaIS8_EEEUlvE_vEEEESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImlE8FillDataEPSt6vectorINS4_17RowBlockContainerImlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjlE8FillDataEPSt6vectorINS4_17RowBlockContainerIjlEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImiE8FillDataEPSt6vectorINS4_17RowBlockContainerImiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjiE8FillDataEPSt6vectorINS4_17RowBlockContainerIjiEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseImfE8FillDataEPSt6vectorINS4_17RowBlockContainerImfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EESt23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc4data14TextParserBaseIjfE8FillDataEPSt6vectorINS4_17RowBlockContainerIjfEESaIS9_EEEUlvE_vEEEESaISG_ELN9__gnu_cxx12_Lock_policyE2EEN4dmlc12RowBlockIterIjfEEN4dmlc8DataIterINS_8RowBlockImfEEEEN4dmlc12RowBlockIterImfEEN4dmlc8DataIterINS_8RowBlockIjiEEEEN4dmlc12RowBlockIterIjiEEN4dmlc8DataIterINS_8RowBlockImiEEEEN4dmlc12RowBlockIterImiEEN4dmlc8DataIterINS_8RowBlockIjlEEEEN4dmlc12RowBlockIterIjlEEN4dmlc8DataIterINS_8RowBlockImlEEEEN4dmlc12RowBlockIterImlEEN4dmlc6ParserImfEEN4dmlc6ParserIjiEEN4dmlc6ParserImiEEN4dmlc6ParserIjlEEN4dmlc6ParserImlEEN4dmlc8DataIterINS_4data17RowBlockContainerIjfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjfEEEEN4dmlc4data11DiskRowIterIjfEEN4dmlc4data12BasicRowIterIjfEEN4dmlc8DataIterINS_4data17RowBlockContainerImfEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImfEEEEN4dmlc4data11DiskRowIterImfEEN4dmlc4data12BasicRowIterImfEEN4dmlc8DataIterINS_4data17RowBlockContainerIjiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjiEEEEN4dmlc4data11DiskRowIterIjiEEN4dmlc4data12BasicRowIterIjiEEN4dmlc8DataIterINS_4data17RowBlockContainerImiEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImiEEEEN4dmlc4data11DiskRowIterImiEEN4dmlc4data12BasicRowIterImiEEN4dmlc8DataIterINS_4data17RowBlockContainerIjlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerIjlEEEEN4dmlc4data11DiskRowIterIjlEEN4dmlc4data12BasicRowIterIjlEEN4dmlc8DataIterINS_4data17RowBlockContainerImlEEEEN4dmlc12ThreadedIterINS_4data17RowBlockContainerImlEEEEN4dmlc4data11DiskRowIterImlEEN4dmlc4data12BasicRowIterImlEEN4dmlc4data10ParserImplIjfEEN4dmlc4data14TextParserBaseIjfEEN4dmlc4data12LibSVMParserIjfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerIjfEESaIS4_EEEEN4dmlc4data14ThreadedParserIjfEEN4dmlc4data10ParserImplImfEEN4dmlc4data14TextParserBaseImfEEN4dmlc4data12LibSVMParserImfEEN4dmlc8DataIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc12ThreadedIterISt6vectorINS_4data17RowBlockContainerImfEESaIS4_EEEEN4dmlc4data14ThreadedParserImfEEN4dmlc4data11LibFMParserIjfEEN4dmlc4data11LibFMParserImfEEN4dmlc4data9CSVParserIjfEEN4dmlc4data9CSVParserImfEEN4dmlc4data10ParserImplIjiEEN4dmlc4data14TextParserBaseIjiEEN4dmlc4data9CSVParserIjiEEN4dmlc4data10ParserImplImiEEN4dmlc4data14TextParserBaseImiEEN4dmlc4data9CSVParserImiEEN4dmlc4data10ParserImplIjlEEN4dmlc4data14TextParserBaseIjlEEN4dmlc4data9CSVParserIjlEEN4dmlc4data10ParserImplImlEEN4dmlc4data14TextParserBaseImlEEN4dmlc4data9CSVParserImlEEZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlPPSt6vectorINS0_17RowBlockContainerIjfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserIjfEC4EPNS0_10ParserImplIjfEEEUlvE0_NSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterISt6vectorINS2_4data17RowBlockContainerIjfEESaIS7_EEE4InitESt8functionIFbPPS9_EESB_IFvvEEEUlvE_vEEEEZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlPPSt6vectorINS0_17RowBlockContainerImfEESaIS8_EEE_ZN4dmlc4data14ThreadedParserImfEC4EPNS0_10ParserImplImfEEEUlvE0_NSt6thre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compile with DMLC_USE_AZURE=1 to use AzurePlease compile with DMLC_USE_HDFS=1 to use hdfsPlease compile with DMLC_USE_S3=1 to use S3/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/single_file_split.hCheck failed: part_index == 0 && num_parts == 1/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/cached_input_split.hCheck failed: nread == sizeof(size) has invalid cache file formatCheck failed: fi_->Read(p->begin, size) == sizeInputSplit do not support writeResetPartition is not supported in CachedInputSplitSingleFileSplit: fail to open invalid input parameter for InputSplit::Createneed to pass index file to use IndexedRecordIOFailed to initialize CachedIterCheck failed: this->InitCachedIter()file://viewfs://s3://http://https://azure://unknown filesystem protocol hdfs://BeforeFirst is not supportedstdinCheck failed: fp_ != NULLCheck failed: part < nsplitindexed_recordiounknown input split type rbFvvEN4dmlc10InputSplitEN4dmlc2io15SingleFileSplitEN4dmlc8DataIterINS_2io14InputSplitBase5ChunkEEEN4dmlc12ThreadedIterINS_2io14InputSplitBase5ChunkEEEN4dmlc2io16CachedInputSplitEN4dmlc2io18ThreadedInputSplitEZN4dmlc2io16CachedInputSplit15InitPreprocIterEvEUlPPNS0_14InputSplitBase5ChunkEE_PFvvENSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS2_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS6_EES8_IFvvEEEUlvE_vEEEEZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlPPNS0_14InputSplitBase5ChunkEE_ZN4dmlc2io16CachedInputSplit14InitCachedIterEvEUlvE0_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlPPNS2_5ChunkEE_ZN4dmlc2io18ThreadedInputSplitC4EPNS0_14InputSplitBaseEmEUlvE0_St23_Sp_counted_ptr_inplaceINSt6thread5_ImplISt12_Bind_simpleIFZN4dmlc12ThreadedIterINS3_2io14InputSplitBase5ChunkEE4InitESt8functionIFbPPS7_EES9_IFvvEEEUlvE_vEEEESaISJ_ELN9__gnu_cxx12_Lock_policyE2EECheck failed: begin != end/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/line_split.ccN4dmlc2io12LineSplitterEinvalid record io formatCheck failed: p >= pbegin + 2Invalid RecordIO FormatCheck failed: cflag == 1U/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/recordio_split.ccCheck failed: fi->Read(&lrec, sizeof(lrec)) != 0(reinterpret_cast<size_t>(begin) & 3UL) == 0U(reinterpret_cast<size_t>(end) & 3UL) == 0UCheck failed: chunk->begin + 2 * sizeof(uint32_t) <= chunk->end(reinterpret_cast<size_t>(chunk->begin) & 3UL) == 0U(reinterpret_cast<size_t>(chunk->end) & 3UL) == 0UCheck failed: chunk->begin <= chunk->endCheck failed: p[0] == RecordIOWriter::kMagicN4dmlc2io16RecordIOSplitterEexpanded_list.size() == 1ul/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/indexed_recordio_split.ccIndexedRecordIOSplitter does not support multiple index filesN4dmlc2io23IndexedRecordIOSplitterE/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/input_split_base.ccCheck failed: offset_end_ >file_offset_[file_ptr_end_]Check failed: file_ptr_end_ < files_.size()file offset not calculated correctlyThis could due to compiler version, g++-4.9 is neededCannot find any files that matches the URI pattern Check failed: files_[i].size % align_bytes == 0curr=,begin=,end=,fileptr=,fileoffset=offset[^$\.*+?()[]{}|.[\*^$.[\()*+?{|^$.[\*^$ .[\()*+?{|^$ -Nothing to repeat before a quantifier.Number of NFA states exceeds limit. Please use shorter regex string, or use smaller brace expression, or make _GLIBCXX_REGEX_STATE_LIMIT larger.Unexpected back-reference in polynomial mode.Back-reference index exceeds current sub-expression count.Back-reference referred to an opened sub-expression.uuv0v@v`vv(wHwxwuwPu||lL,T$̀|DInvalid character class.Unexpected token in brace expression.Unexpected end of brace expression.Invalid range in brace expression.Invalid collate element.Invalid equivalence class.Unexpected dash in bracket expression. For POSIX syntax, a dash is not treated literally only when it is at beginning or end.Invalid range in bracket expression.Character is expected after a dash.Unexpected character in bracket expression.Parenthesis is not closed.N4dmlc2io14InputSplitBaseESt23_Sp_counted_ptr_inplaceINSt8__detail4_NFAINSt7__cxx1112regex_traitsIcEEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEEww error: LocalFileSystem.GetPathInfo: stdoutwbCheck failed: allow_null LocalFileSystem::Open "../home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/local_filesys.ccLocalFileSystem.GetPathInfo: detected symlink LocalFileSystem.ListDirectory Check failed: std::fwrite(ptr, 1, size, fp_) == sizeFileStream.Write incompleteCheck failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET)N4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamElstat(path.c_str(), &sb) == 0Couldn't remove file ~TemporaryDirectory(): /home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/include/dmlc/filesystem.hdmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/home/runner/work/ml-test-builds/ml-test-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectory; you may want to remove it manuallySuccessfully deleted temporary directory Could not remove temporary directory N4dmlc2io10FileSystemEcannot initialize reduce handle twicethe rabit has not been initializedmust intialize handle to call AllReducerabit::Finalize engine is not initialized or already been finalized.Read pickle stringnot implementedDataType does not support bitwise or operationunknown data_typeunknown enum_opt,Dt4dD4dDt,\N5rabit5c_api11ReadWrapperEN5rabit5c_api12WriteWrapperEInitAfterException: not implementedrabit_tracker_urirabit_tracker_portrabit_task_idDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_TASK_IDDMLC_ROLErabit_world_sizerabit_hadoop_moderabit_reduce_ring_mincount%lu%cinvalid format for %srabit_reduce_bufferDMLC_WORKER_CONNECT_RETRYCreatecannot obtain address of %sDoes not support IPv6connect to (failed): [%s] -ConnectSendAllReConnectLink failure 1RecvAllReConnectLink failure 2ReConnectLink failure 3error during send SendStrworker256MBReConnectLink failure 4SetKeepAliveSO_LINGER0.0.0.0TryBindHostGetSockErrorReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8error during send RecvStrReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure 14AcceptReConnectLink failure 15ReConnectLink: bad socketSetNonBlock-1SetNonBlock-2%[^=]=%smapred_tip_idmapreduce_task_idmapred_task_id%drabit_num_trialmapred_map_tasksmapreduce_job_mapscan only call Init oncefail to get host namestartneed to assume rank structurePollwrite ptr boundary checkAllreduce: boundary check[%d] read_ptr boundary checkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorinvalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}retry connect to ip(retry time %d): [%s] -sync::Invalid tracker message, init failureSocket::Close double close the socket or close without createmust keep rank to same if the node already have oneReConnectLink fail to bind the ports specifiedReConnectLink failure, link rank inconsistentOverride a link that is activecannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkhadoop_mode is set but cannot find mapred_task_idhadoop_mode is set but cannot find mapred_map_tasksRabit Module currently only work with dmlc worker, quit this program by exit 0 -too large type_nbytes=%lu, buffer_size=%luReadToRingBuffer: buffer not allocatedReadToRingBuffer: max_size_read checkBroadcast: root should be smaller than world sizeSocket %s Error:%sBroadcast failedAllreduce failedN5rabit6engine7IEngineEN5rabit6engine13AllreduceBaseErabit_reduce_bufrabit_reduce_rinrabit_tracker_urrabit_tracker_poDMLC_NUM_ATTEMPTDMLC_TRACKER_URIDMLC_TRACKER_PORDMLC_WORKER_CONNrabit_global_replicarabit_local_replicamust know the error sourcemust already gone badwrong oob msgshould already read past markBUGwrong Ack MSGRingPassing: boundary check1RingPassing: boundary check2RingPassing: boundary check3invalid local replicaparent must be 0invalie stage idMsgPassing invalid stagerequest result inconsistentTryRecoverDataTryDecideRoutingrecv_link must be activeTryGetResult::Checkpointmin seq bugcannot allocate 0 size memoryPushTemp seqid inconsistentPushTemp inconsistentread in version numbercheck ack must return truecheck point must return truerecoverCan only call Checkpoint/LoadCheckPoint always withor without local_model, but not mixed caselocal chkpt space inconsistentTryCheckinLocalState must have exactly 1 state[%d] Allreduce size inconsistent, distin=%lu, size=%lu, reporting=%lu + bad regex files_.size() != 0Ufile do not align by bytesNULSOHSTXETXEOTENQACKalertbackspacenewlinevertical-tabform-feedcarriage-returnSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCIS4IS3IS2IS1exclamation-markquotation-marknumber-signdollar-signpercent-signampersandapostropheleft-parenthesisright-parenthesisasteriskplus-signcommahyphenperiodzeroonetwothreefourfivesixsevenninesemicolonless-than-signequals-signgreater-than-signquestion-markcommercial-atAFJPSVWleft-square-bracketbackslashright-square-bracketcircumflexunderscoregrave-accentjuzleft-curly-bracketvertical-lineright-curly-brackettildeDELalnumblankcntrlgraphlowerprintpunctupperxdigiť4D܏d4LN4dmlc2io14InputSplitBaseESt23_Sp_counted_ptr_inplaceINSt8__detail4_NFAINSt7__cxx1112regex_traitsIcEEEESaIS5_ELN9__gnu_cxx12_Lock_policyE2EENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0ELb1EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb0EEENSt8__detail11_AnyMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail12_CharMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb0ELb1EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb0EEENSt8__detail15_BracketMatcherINSt7__cxx1112regex_traitsIcEELb1ELb1EEEwFileStream.Write incompletestdoutwbCheck failed: allow_null LocalFileSystem::Open " error: LocalFileSystem.GetPathInfo: ../home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/local_filesys.ccCheck failed: std::fwrite(ptr, 1, size, fp_) == sizeCheck failed: !std::fseek(fp_, static_cast<long>(pos), SEEK_SET)LocalFileSystem.GetPathInfo: detected symlink LocalFileSystem.ListDirectory N4dmlc2io15LocalFileSystemEN4dmlc2io10FileStreamElstat(path.c_str(), &sb) == 0Couldn't remove file ~TemporaryDirectory(): /home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/include/dmlc/filesystem.hdmlc::TemporaryDirectory::IsSymlink(): Unable to read file attributes/home/runner/work/ml-builds/ml-builds/xgboost/dmlc-core/src/io/filesys.ccCheck failed: !IsSymlink(info.path.name)Symlink not supported in TemporaryDirectory; you may want to remove it manuallySuccessfully deleted temporary directory Could not remove temporary directory N4dmlc2io10FileSystemEcannot initialize reduce handle twicerabit::Finalize engine is not initialized or already been finalized.the rabit has not been initializedmust intialize handle to call AllReduceRead pickle stringnot implementedunknown data_typeunknown enum_opDataType does not support bitwise or operationp@`0p`0 P `0N5rabit5c_api11ReadWrapperEN5rabit5c_api12WriteWrapperErabit_tracker_urirabit_tracker_portrabit_task_idDMLC_TRACKER_URIDMLC_TRACKER_PORTDMLC_TASK_IDDMLC_ROLErabit_world_sizerabit_hadoop_moderabit_reduce_ring_mincount%lu%cinvalid format for %srabit_reduce_bufferDMLC_WORKER_CONNECT_RETRYSocket %s Error:%s0.0.0.0cannot obtain address of %sDoes not support IPv6TryBindHostCreateconnect to (failed): [%s] +ConnectSendAllReConnectLink failure 1RecvAllReConnectLink failure 2ReConnectLink failure 3error during send SendStrPollAllreduce: boundary checkbuffer size inconsistentmust assign buffer_sizeAllreduce: size checkAllreduce: boundary errorneed to assume rank structurewrite ptr boundary check[%d] read_ptr boundary checkAllreduce failedBroadcast failedworker256MBReConnectLink failure 4SetKeepAliveSO_LINGERGetSockErrorReConnectLink failure 5ReConnectLink failure 6ReConnectLink failure 7ReConnectLink failure 8error during send RecvStrReConnectLink failure 9ReConnectLink failure 10ReConnectLink failure 12ReConnectLink failure 13ReConnectLink failure 14AcceptReConnectLink failure 15ReConnectLink: bad socketSetNonBlock-1SetNonBlock-2mapred_tip_id%[^=]=%smapreduce_task_idmapred_task_id%dmapred_map_tasksmapreduce_job_mapscan only call Init oncefail to get host namestartrabit_num_trialInitAfterException: not implementedinvalid format for %s,shhould be {integer}{unit}, unit can be {B, KB, MB, GB}Socket::Close double close the socket or close without createretry connect to ip(retry time %d): [%s] +sync::Invalid tracker message, init failuretoo large type_nbytes=%lu, buffer_size=%luReadToRingBuffer: buffer not allocatedReadToRingBuffer: max_size_read checkBroadcast: root should be smaller than world sizemust keep rank to same if the node already have oneReConnectLink fail to bind the ports specifiedReConnectLink failure, link rank inconsistentOverride a link that is activecannot find parent in the linkcannot find prev ring in the linkcannot find next ring in the linkhadoop_mode is set but cannot find mapred_task_idhadoop_mode is set but cannot find mapred_map_tasksRabit Module currently only work with dmlc worker, quit this program by exit 0 +N5rabit6engine7IEngineEN5rabit6engine13AllreduceBaseErabit_global_replicarabit_local_replicarecovermust know the error sourcemust already gone badwrong oob msgshould already read past markBUGwrong Ack MSGRingPassing: boundary check1RingPassing: boundary check2RingPassing: boundary check3TryDecideRoutingrecv_link must be activeTryRecoverDatainvalid local replicavector<bool>::_M_fill_insertparent must be 0invalie stage idMsgPassing invalid stagerequest result inconsistentTryGetResult::Checkpointmin seq bugcannot allocate 0 size memoryPushTemp seqid inconsistentPushTemp inconsistentread in version numbercheck ack must return truecheck point must return trueCan only call Checkpoint/LoadCheckPoint always withor without local_model, but not mixed caseTryCheckinLocalState must have exactly 1 statelocal chkpt space inconsistent[%d] Allreduce size inconsistent, distin=%lu, size=%lu, reporting=%lu Too many nodes went down and we cannot recover..cannot get and receive request[%d] recovered from local checkpoint version %d LoadCheckPoint: too many nodes fails, cannot recover local statezero size check point is not allowedAllreduce Recovered data size do not match the specification of function call. 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