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2024-09-11T10:19:09.5771275Z =================================== FAILURES ===================================
2024-09-11T10:19:09.5771711Z _____________ TestScatterGatherXPU.test_scatter_add__xpu_complex64 _____________
2024-09-11T10:19:09.5772085Z Traceback (most recent call last):
2024-09-11T10:19:09.5772925Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 197, in test_scatter_add_
2024-09-11T10:19:09.5773720Z self._test_scatter_base(torch.Tensor.scatter_add_, device=device, dtype=dtype,
2024-09-11T10:19:09.5774679Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 110, in _test_scatter_base
2024-09-11T10:19:09.5775350Z actual = fn(base.clone(), dim, idx, src)
2024-09-11T10:19:09.5776938Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5778235Z 2024-09-11T10:19:09.5778398Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5778984Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_add__xpu_complex642024-09-11T10:19:09.5779399Z 2024-09-11T10:19:09.5779604Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5783397Z ______________ TestScatterGatherXPU.test_scatter_add__xpu_float16 ______________2024-09-11T10:19:09.5783840Z Traceback (most recent call last):2024-09-11T10:19:09.5784698Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 197, in test_scatter_add_2024-09-11T10:19:09.5785707Z self._test_scatter_base(torch.Tensor.scatter_add_, device=device, dtype=dtype,2024-09-11T10:19:09.5786704Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 110, in _test_scatter_base2024-09-11T10:19:09.5787421Z actual = fn(base.clone(), dim, idx, src)2024-09-11T10:19:09.5789091Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5790424Z
2024-09-11T10:19:09.5790595Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5791164Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_add__xpu_float16
2024-09-11T10:19:09.5791588Z
2024-09-11T10:19:09.5792149Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5792618Z ______________ TestScatterGatherXPU.test_scatter_add__xpu_float32 ______________
2024-09-11T10:19:09.5793035Z Traceback (most recent call last):
2024-09-11T10:19:09.5793783Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 197, in test_scatter_add_
2024-09-11T10:19:09.5794543Z self._test_scatter_base(torch.Tensor.scatter_add_, device=device, dtype=dtype,
2024-09-11T10:19:09.5795403Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 110, in _test_scatter_base
2024-09-11T10:19:09.5796064Z actual = fn(base.clone(), dim, idx, src)
2024-09-11T10:19:09.5797630Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5798875Z 2024-09-11T10:19:09.5799048Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5799603Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_add__xpu_float322024-09-11T10:19:09.5800016Z 2024-09-11T10:19:09.5800211Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5800702Z ______ TestScatterGatherXPU.test_scatter_add_mult_index_base_xpu_float32 _______2024-09-11T10:19:09.5801079Z Traceback (most recent call last):2024-09-11T10:19:09.5801872Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 207, in test_scatter_add_mult_index_base2024-09-11T10:19:09.5802684Z res0 = torch.zeros(m, n, device=device, dtype=dtype).scatter_add_(0, idx, src)2024-09-11T10:19:09.5804350Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5805603Z
2024-09-11T10:19:09.5805772Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5806377Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_add_mult_index_base_xpu_float32
2024-09-11T10:19:09.5806864Z
2024-09-11T10:19:09.5807057Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5807571Z __________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_bfloat16 __________
2024-09-11T10:19:09.5807938Z Traceback (most recent call last):
2024-09-11T10:19:09.5808700Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean
2024-09-11T10:19:09.5809492Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,
2024-09-11T10:19:09.5810382Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base
2024-09-11T10:19:09.5811162Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)
2024-09-11T10:19:09.5812858Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5814135Z 2024-09-11T10:19:09.5814293Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5815039Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_bfloat162024-09-11T10:19:09.5815462Z 2024-09-11T10:19:09.5815667Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5816143Z __________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float16 ___________2024-09-11T10:19:09.5816519Z Traceback (most recent call last):2024-09-11T10:19:09.5817282Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean2024-09-11T10:19:09.5818077Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,2024-09-11T10:19:09.5818950Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base2024-09-11T10:19:09.5819731Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)2024-09-11T10:19:09.5821420Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5822686Z
2024-09-11T10:19:09.5822855Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5823441Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float16
2024-09-11T10:19:09.5823869Z
2024-09-11T10:19:09.5824067Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5824550Z __________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float32 ___________
2024-09-11T10:19:09.5824916Z Traceback (most recent call last):
2024-09-11T10:19:09.5825681Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean
2024-09-11T10:19:09.5826475Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,
2024-09-11T10:19:09.5827348Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base
2024-09-11T10:19:09.5828196Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)
2024-09-11T10:19:09.5829871Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5831138Z 2024-09-11T10:19:09.5831324Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5831915Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float322024-09-11T10:19:09.5832334Z 2024-09-11T10:19:09.5832527Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5833008Z __________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float64 ___________2024-09-11T10:19:09.5833386Z Traceback (most recent call last):2024-09-11T10:19:09.5834189Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean2024-09-11T10:19:09.5834981Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,2024-09-11T10:19:09.5835846Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base2024-09-11T10:19:09.5836623Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)2024-09-11T10:19:09.5838279Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5839530Z
2024-09-11T10:19:09.5839690Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5840275Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_float64
2024-09-11T10:19:09.5840709Z
2024-09-11T10:19:09.5840903Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5841380Z ___________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int16 ____________
2024-09-11T10:19:09.5841748Z Traceback (most recent call last):
2024-09-11T10:19:09.5842509Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean
2024-09-11T10:19:09.5843301Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,
2024-09-11T10:19:09.5844172Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base
2024-09-11T10:19:09.5844937Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)
2024-09-11T10:19:09.5846614Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5847870Z 2024-09-11T10:19:09.5848059Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5848676Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int162024-09-11T10:19:09.5849094Z 2024-09-11T10:19:09.5849287Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5849767Z ___________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int32 ____________2024-09-11T10:19:09.5850144Z Traceback (most recent call last):2024-09-11T10:19:09.5850926Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean2024-09-11T10:19:09.5851715Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,2024-09-11T10:19:09.5852583Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base2024-09-11T10:19:09.5853362Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)2024-09-11T10:19:09.5855111Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5856378Z
2024-09-11T10:19:09.5856542Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5857130Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int32
2024-09-11T10:19:09.5857554Z
2024-09-11T10:19:09.5857745Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5858222Z ___________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int64 ____________
2024-09-11T10:19:09.5858586Z Traceback (most recent call last):
2024-09-11T10:19:09.5859353Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean
2024-09-11T10:19:09.5860148Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,
2024-09-11T10:19:09.5861003Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base
2024-09-11T10:19:09.5861780Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)
2024-09-11T10:19:09.5863457Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5864721Z 2024-09-11T10:19:09.5864883Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5865467Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int642024-09-11T10:19:09.5865882Z 2024-09-11T10:19:09.5866075Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5866553Z ____________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int8 ____________2024-09-11T10:19:09.5866929Z Traceback (most recent call last):2024-09-11T10:19:09.5867674Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean2024-09-11T10:19:09.5868501Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,2024-09-11T10:19:09.5869400Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base2024-09-11T10:19:09.5870184Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)2024-09-11T10:19:09.5871880Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.
2024-09-11T10:19:09.5873143Z
2024-09-11T10:19:09.5873302Z To execute this test, run the following from the base repo dir:
2024-09-11T10:19:09.5873881Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_int8
2024-09-11T10:19:09.5874304Z
2024-09-11T10:19:09.5874497Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
2024-09-11T10:19:09.5875001Z ___________ TestScatterGatherXPU.test_scatter_reduce_mean_xpu_uint8 ____________
2024-09-11T10:19:09.5875373Z Traceback (most recent call last):
2024-09-11T10:19:09.5876131Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 237, in test_scatter_reduce_mean
2024-09-11T10:19:09.5876930Z self._test_scatter_base(torch.Tensor.scatter_reduce_, device=device, dtype=dtype,
2024-09-11T10:19:09.5877785Z File "/home/sdp/actions-runner-1/_work/torch-xpu-ops/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_scatter_gather_ops.py", line 106, in _test_scatter_base
2024-09-11T10:19:09.5878563Z actual = fn(base.clone(), dim, idx, src, reduce=reduction, include_self=include_self)
2024-09-11T10:19:09.5880241Z RuntimeError: scatter_add_kernel does not have a deterministic implementation, but you set'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation.2024-09-11T10:19:09.5881495Z 2024-09-11T10:19:09.5881653Z To execute this test, run the following from the base repo dir:2024-09-11T10:19:09.5882236Z PYTORCH_TEST_WITH_SLOW=1 python test/test_scatter_gather_ops.py TestScatterGatherXPU.test_scatter_reduce_mean_xpu_uint82024-09-11T10:19:09.5882649Z 2024-09-11T10:19:09.5882841Z This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=02024-09-11T10:19:09.5883269Z =========================== short test summary info ============================
The text was updated successfully, but these errors were encountered:
🚀 The feature, motivation and pitch
The issue is introduced in codegen pr #310.
The FAILED UT throw errors like
The affected UTs include
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Detail failed logs
The text was updated successfully, but these errors were encountered: