Блог

Я выполнил новую установку лямбда-стека. После того, как я проверил, что tensorflow-gpu действительно работает, я попробовал запустить ai-benchmark (https://pypi.org/project/ai-benchmark /) но это не работает.

Результат выглядит следующим образом:

 Python 3.8.5 (default, Jul 28 2020, 12:59:40) 
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from ai_benchmark import AIBenchmark
2020-11-25 15:25:07.660243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:07.663124: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Invalid MIT-MAGIC-COOKIE-1 key>>> results = AIBenchmark().run()

>>   AI-Benchmark-v.0.1.2   
>>   Let the AI Games begin..

2020-11-25 15:25:24.179548: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 3693055000 Hz
2020-11-25 15:25:24.180403: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1a945d0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-11-25 15:25:24.180460: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-11-25 15:25:24.184604: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-11-25 15:25:24.261100: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.261618: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0xe68480 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-11-25 15:25:24.261652: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce GTX 1080, Compute Capability 6.1
2020-11-25 15:25:24.261992: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.262970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1080 computeCapability: 6.1
coreClock: 1.7335GHz coreCount: 20 deviceMemorySize: 7.93GiB deviceMemoryBandwidth: 298.32GiB/s
2020-11-25 15:25:24.263022: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:24.266092: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-25 15:25:24.267408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-25 15:25:24.267768: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-25 15:25:24.271212: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-25 15:25:24.272057: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-25 15:25:24.272208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:24.272364: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.273190: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.273858: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-11-25 15:25:24.590979: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-25 15:25:24.591018: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]      0 
2020-11-25 15:25:24.591023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0:   N 
2020-11-25 15:25:24.591243: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.591711: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.592105: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/device:GPU:0 with 7018 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-11-25 15:25:24.592836: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.593239: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1080 computeCapability: 6.1
coreClock: 1.7335GHz coreCount: 20 deviceMemorySize: 7.93GiB deviceMemoryBandwidth: 298.32GiB/s
2020-11-25 15:25:24.593258: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:24.593294: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-25 15:25:24.593306: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-25 15:25:24.593316: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-25 15:25:24.593327: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-25 15:25:24.593337: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-25 15:25:24.593347: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:24.593398: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.593806: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.594170: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-11-25 15:25:24.594193: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-25 15:25:24.594199: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]      0 
2020-11-25 15:25:24.594203: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0:   N 
2020-11-25 15:25:24.594272: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.594681: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.595055: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/device:GPU:0 with 7018 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-11-25 15:25:24.595330: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.595714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1080 computeCapability: 6.1
coreClock: 1.7335GHz coreCount: 20 deviceMemorySize: 7.93GiB deviceMemoryBandwidth: 298.32GiB/s
2020-11-25 15:25:24.595730: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:24.595756: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-25 15:25:24.595766: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-25 15:25:24.595777: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-25 15:25:24.595787: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-25 15:25:24.595796: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-25 15:25:24.595806: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:24.595853: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.596259: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.596622: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-11-25 15:25:24.596641: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-25 15:25:24.596646: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]      0 
2020-11-25 15:25:24.596651: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0:   N 
2020-11-25 15:25:24.596716: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.597125: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:24.597497: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/device:GPU:0 with 7018 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
*  TF Version: 2.3.1
*  Platform: Linux-5.4.0-54-generic-x86_64-with-glibc2.29
*  CPU: N/A
*  CPU RAM: 16 GB
*  GPU/0: GeForce GTX 1080
*  GPU RAM: 6.9 GB
*  CUDA Version: 11.1
*  CUDA Build: V11.1.74

The benchmark is running...
The tests might take up to 20 minutes
Please dont interrupt the script

1/19. MobileNet-V2

2020-11-25 15:25:31.191492: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.192235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1080 computeCapability: 6.1
coreClock: 1.7335GHz coreCount: 20 deviceMemorySize: 7.93GiB deviceMemoryBandwidth: 298.32GiB/s
2020-11-25 15:25:31.192286: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:31.192354: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-25 15:25:31.192387: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-25 15:25:31.192418: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-25 15:25:31.192448: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-25 15:25:31.192474: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-25 15:25:31.192500: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:31.192644: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.193372: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.194012: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-11-25 15:25:31.194810: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.195522: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1080 computeCapability: 6.1
coreClock: 1.7335GHz coreCount: 20 deviceMemorySize: 7.93GiB deviceMemoryBandwidth: 298.32GiB/s
2020-11-25 15:25:31.195556: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-25 15:25:31.195604: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-25 15:25:31.195632: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-25 15:25:31.195658: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-25 15:25:31.195681: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-25 15:25:31.195700: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-25 15:25:31.195724: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:31.195822: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.196510: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.197127: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-11-25 15:25:31.197169: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-25 15:25:31.197181: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]      0 
2020-11-25 15:25:31.197193: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0:   N 
2020-11-25 15:25:31.197330: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.198053: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-11-25 15:25:31.198703: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7018 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-11-25 15:25:32.271855: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-25 15:25:32.835532: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
1.1 - inference | batch=50, size=224x224: 57.9 ± 1.5 ms
Could not load library libcudnn_cnn_train.so.8. Error: libcudnn_ops_train.so.8: cannot open shared object file: No such file or directory
Please make sure libcudnn_cnn_train.so.8 is in your library path!
[MINI:25659] *** Process received signal ***
[MINI:25659] Signal: Aborted (6)
[MINI:25659] Signal code:  (-6)
[MINI:25659] [ 0] /lib/x86_64-linux-gnu/libc.so.6( 0x46210)[0x7fd617cd0210]
[MINI:25659] [ 1] /lib/x86_64-linux-gnu/libc.so.6(gsignal 0xcb)[0x7fd617cd018b]
[MINI:25659] [ 2] /lib/x86_64-linux-gnu/libc.so.6(abort 0x12b)[0x7fd617caf859]
[MINI:25659] [ 3] /usr/lib/python3/dist-packages/tensorflow/python/../libcudnn.so.8(cudnnGetConvolutionBackwardFilterWorkspaceSize 0xc9)[0x7fd5a4089959]
[MINI:25659] [ 4] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2(cudnnGetConvolutionBackwardFilterWorkspaceSize 0x5f)[0x7fd5da35f9cf]
[MINI:25659] [ 5] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2( 0x1516c4d)[0x7fd5da340c4d]
[MINI:25659] [ 6] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2(_ZN15stream_executor3gpu12CudnnSupport23DoPrepareForConvolutionENS_3dnn15ConvolutionKindENS2_8DataTypeEPNS_6StreamERKNS2_15BatchDescriptorENS_16DeviceMemoryBaseERKNS2_16FilterDescriptorESA_S9_SA_RKNS2_21ConvolutionDescriptorERKNS2_15AlgorithmConfigEPNS_16ScratchAllocatorEPNS2_13AlgorithmDescEPNS_12DeviceMemoryIhEE 0xfc9)[0x7fd5da34bdd9]
[MINI:25659] [ 7] /usr/lib/python3/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.cpython-38-x86_64-linux-gnu.so(_ZN15stream_executor6Stream39ThenConvolveBackwardFilterWithAlgorithmERKNS_3dnn15BatchDescriptorERKNS_12DeviceMemoryIfEES4_S6_RKNS1_21ConvolutionDescriptorERKNS1_16FilterDescriptorEPS6_PNS_16ScratchAllocatorERKNS1_15AlgorithmConfigEPNS1_13ProfileResultE 0xa4b)[0x7fd5f1a781ab]
[MINI:25659] [ 8] /usr/lib/python3/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.cpython-38-x86_64-linux-gnu.so(_ZN10tensorflow28LaunchConv2DBackpropFilterOpIN5Eigen9GpuDeviceEfEclEPNS_15OpKernelContextEbbRKNS_6TensorES8_iiiiRKNS_7PaddingERKSt6vectorIxSaIxEEPS6_NS_12TensorFormatE 0x1a18)[0x7fd5edc5e4b8]
[MINI:25659] [ 9] /usr/lib/python3/dist-packages/tensorflow/python/_pywrap_tensorflow_internal.cpython-38-x86_64-linux-gnu.so(_ZN10tensorflow22Conv2DBackpropFilterOpIN5Eigen9GpuDeviceEfE7ComputeEPNS_15OpKernelContextE 0x23b)[0x7fd5edc5f8bb]
[MINI:25659] [10] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2(_ZN10tensorflow13BaseGPUDevice7ComputeEPNS_8OpKernelEPNS_15OpKernelContextE 0x245)[0x7fd5d9e47675]
[MINI:25659] [11] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2( 0x10e2307)[0x7fd5d9f0c307]
[MINI:25659] [12] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2( 0x10e3c13)[0x7fd5d9f0dc13]
[MINI:25659] [13] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2(_ZN5Eigen15ThreadPoolTemplIN10tensorflow6thread16EigenEnvironmentEE10WorkerLoopEi 0x2a5)[0x7fd5d9facf75]
[MINI:25659] [14] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2(_ZNSt17_Function_handlerIFvvEZN10tensorflow6thread16EigenEnvironment12CreateThreadESt8functionIS0_EEUlvE_E9_M_invokeERKSt9_Any_data 0x47)[0x7fd5d9fa9f57]
[MINI:25659] [15] /usr/lib/python3/dist-packages/tensorflow/python/../libtensorflow_framework.so.2( 0x1171cef)[0x7fd5d9f9bcef]
[MINI:25659] [16] /lib/x86_64-linux-gnu/libpthread.so.0( 0x9609)[0x7fd617c70609]
[MINI:25659] [17] /lib/x86_64-linux-gnu/libc.so.6(clone 0x43)[0x7fd617dac293]
[MINI:25659] *** End of error message ***
Aborted (core dumped)

 

Может ли кто-нибудь указать мне правильное направление? Большое спасибо.

Пожалуйста, простите за следующее, мне сказали, что мой пост в основном состоит из кода, поэтому я должен увеличить свой текст.

«Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.»

Could not load library libcudnn_cnn_train.so.8. Error: libcudnn_ops_train.so.8: cannot open shared object file: No such file or directory это важная строка.

Во-первых, вам необходимо убедиться, что у вас есть соответствующий файл libcudnn на вашем компьютере (с помощью find или locate ). Если вы этого не сделаете, вам нужно их загрузить.

Затем вам нужно убедиться, что ваши переменные PATH / LD_LIBRARY_PATH указывают на каталоги, содержащие эти файлы.

Это обсуждение здесь было 2 года назад и, таким образом, упоминает разные файлы, но в остальной части обсуждения должны быть приведены примеры, на которых основывается ваше исправление: https://github.com/tensorflow/tensorflow/issues/20271