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启动时异常~ #1

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lyman-meng opened this issue Jul 22, 2021 · 1 comment
Open

启动时异常~ #1

lyman-meng opened this issue Jul 22, 2021 · 1 comment

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@lyman-meng
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sppe:file:/C:/Users/pc01/Desktop/SmartClassroomJava-master_new/SmartClassroomJava-master/target/classes/sppe
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
ai.djl.engine.EngineException: Could not run 'aten::empty_strided' with arguments from the 'CUDA' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::empty_strided' is only available for these backends: [CPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradNestedTensor, UNKNOWN_TENSOR_TYPE_ID, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

CPU: registered at aten\src\ATen\RegisterCPU.cpp:5925 [kernel]
BackendSelect: registered at aten\src\ATen\RegisterBackendSelect.cpp:596 [kernel]
Named: registered at ....\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]
AutogradOther: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradCPU: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradCUDA: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradXLA: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradNestedTensor: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
UNKNOWN_TENSOR_TYPE_ID: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse1: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse2: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse3: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
Tracer: registered at ....\torch\csrc\autograd\generated\TraceType_0.cpp:10499 [kernel]
Autocast: fallthrough registered at ....\aten\src\ATen\autocast_mode.cpp:250 [backend fallback]
Batched: registered at ....\aten\src\ATen\BatchingRegistrations.cpp:1016 [backend fallback]
VmapMode: fallthrough registered at ....\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]

============================Close: xyz.hyhy.scai.exemodules.YoloModule@d6b43de
at ai.djl.pytorch.jni.PyTorchLibrary.moduleLoad(Native Method)
at ai.djl.pytorch.jni.JniUtils.loadModule(JniUtils.java:1359)
at ai.djl.pytorch.engine.PtModel.load(PtModel.java:85)
at ai.djl.repository.zoo.BaseModelLoader.loadModel(BaseModelLoader.java:156)
at ai.djl.repository.zoo.Criteria.loadModel(Criteria.java:174)
at ai.djl.repository.zoo.ModelZoo.loadModel(ModelZoo.java:99)
at xyz.hyhy.scai.ml.YoloV5Detector.(YoloV5Detector.java:46)
at xyz.hyhy.scai.exemodules.YoloModule.open(YoloModule.java:25)
at xyz.hyhy.scai.core.modules.BaseModule.run(BaseModule.java:50)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
ai.djl.engine.EngineException: Could not run 'aten::empty_strided' with arguments from the 'CUDA' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::empty_strided' is only available for these backends: [CPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradNestedTensor, UNKNOWN_TENSOR_TYPE_ID, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

CPU: registered at aten\src\ATen\RegisterCPU.cpp:5925 [kernel]
BackendSelect: registered at aten\src\ATen\RegisterBackendSelect.cpp:596 [kernel]
Named: registered at ....\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]
AutogradOther: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradCPU: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradCUDA: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradXLA: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradNestedTensor: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
UNKNOWN_TENSOR_TYPE_ID: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse1: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse2: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
AutogradPrivateUse3: registered at ....\torch\csrc\autograd\generated\VariableType_0.cpp:9273 [autograd kernel]
Tracer: registered at ....\torch\csrc\autograd\generated\TraceType_0.cpp:10499 [kernel]
Autocast: fallthrough registered at ....\aten\src\ATen\autocast_mode.cpp:250 [backend fallback]
Batched: registered at ....\aten\src\ATen\BatchingRegistrations.cpp:1016 [backend fallback]
VmapMode: fallthrough registered at ....\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]

at ai.djl.pytorch.jni.PyTorchLibrary.moduleLoad(Native Method)
at ai.djl.pytorch.jni.JniUtils.loadModule(JniUtils.java:1359)
at ai.djl.pytorch.engine.PtModel.load(PtModel.java:85)
at ai.djl.repository.zoo.BaseModelLoader.loadModel(BaseModelLoader.java:156)
at ai.djl.repository.zoo.Criteria.loadModel(Criteria.java:174)
at ai.djl.repository.zoo.ModelZoo.loadModel(ModelZoo.java:99)
at xyz.hyhy.scai.ml.ParallelPoseEstimator.<init>(ParallelPoseEstimator.java:114)
at xyz.hyhy.scai.ml.AlphaPoseEstimator.<init>(AlphaPoseEstimator.java:24)
at xyz.hyhy.scai.exemodules.AlphaPoseModule.open(AlphaPoseModule.java:27)
at xyz.hyhy.scai.core.modules.BaseModule.run(BaseModule.java:50)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

============================Close: xyz.hyhy.scai.exemodules.AlphaPoseModule@6870323
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688
process: 0, wait: 0, name: xyz.hyhy.scai.startmodules.VideoModule@23157688

@0xiyangyang0
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+1请问怎么解决

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