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TensorFlow on AWS

TensorFlow™ is one of many deep learning frameworks available to researchers and developers to enhance their applications with machine learning. AWS provides broad support for TensorFlow, enabling customers to develop and serve their own models across computer vision, natural language processing, speech translation, and more.

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RuntimeError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid

The environment I'm using is: - aws p4dn.24xlarge instance (NVIDIA Ampere A100 GPU ) - cuda 10.1 - tensorflow 2.3.0 - python 3.6.9 I get an error when I run the following. What is the reason? ``` tensorflow.test.is_gpu_available() ``` 2022-01-23 07:56:08.088849: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: pciBusID: 0000:10:1c.0 name: A100-SXM4-40GB computeCapability: 8.0 coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.59GiB deviceMemoryBandwidth: 1.41TiB/s 2022-01-23 07:56:08.088936: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 2022-01-23 07:56:08.089013: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10 2022-01-23 07:56:08.089030: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10 2022-01-23 07:56:08.089046: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10 2022-01-23 07:56:08.089059: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10 2022-01-23 07:56:08.089074: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10 2022-01-23 07:56:08.089090: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7 2022-01-23 07:56:08.092700: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0 Traceback (most recent call last): File "", line 1, in File "/home/ubuntu/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 324, in new_func return func(*args, **kwargs) File "/home/ubuntu/.local/lib/python3.6/site-packages/tensorflow/python/framework/test_util.py", line 1563, in is_gpu_available for local_device in device_lib.list_local_devices(): File "/home/ubuntu/.local/lib/python3.6/site-packages/tensorflow/python/client/device_lib.py", line 43, in list_local_devices _convert(s) for s in _pywrap_device_lib.list_devices(serialized_config) RuntimeError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid
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