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Test Nvidia CUDA environment in relation to TensorFlow
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======================================================
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* `./run` tests the native system. One of tf1 or tf2 is expected to have no
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GPU available due to CUDA library incompatibility
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* `./run-docker` tests Docker support. Both TensorFlow versions should work
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as we're using a base image compatible to the respective version.
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* `./run-docker-compatibility-matrix` tests combinations of (pip-installable)
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TensorFlow versions and `nvidia/cuda` images.
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Example output
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==============
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~~~
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% ./run-docker
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== tensorflow-gpu 1.15 nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04
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GPU 0: NVIDIA GeForce RTX 2080 (UUID: GPU-612ce75c-1340-772b-039c-2a83a3ea5c95)
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TensorFlow 1.15.0
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GPU available: True
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== tensorflow 2.4.3 nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04
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GPU 0: NVIDIA GeForce RTX 2080 (UUID: GPU-612ce75c-1340-772b-039c-2a83a3ea5c95)
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TensorFlow 2.4.3
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GPU available: True
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== tensorflow 2.5.1 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04
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GPU 0: NVIDIA GeForce RTX 2080 (UUID: GPU-612ce75c-1340-772b-039c-2a83a3ea5c95)
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TensorFlow 2.5.1
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GPU available: True
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== tensorflow 2.6.0 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04
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GPU 0: NVIDIA GeForce RTX 2080 (UUID: GPU-612ce75c-1340-772b-039c-2a83a3ea5c95)
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TensorFlow 2.6.0
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GPU available: True
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~~~
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Results
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=======
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As of 2021-10, the only combinations that are working:
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* TensorFlow 1.15.3 using CUDA Toolkit 10.0
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* (TensorFlow 2.3.0 using CUDA Toolkit 10.1)
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* TensorFlow 2.4.3 using CUDA Toolkit 11.0
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* TensorFlow 2.5.1 & TensorFlow 2.6.0 using CUDA Toolkit 11.1 & 11.2.1
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This is only for pip-installable TensorFlow from PyPI, not self-compiled nor
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Anaconda. Note that these are the CUDA *Toolkit* versions, not the CUDA version
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the driver supports (reported by `nvidia-smi`).
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Full log `run-docker-compatibility-matrix`
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------------------------------------------
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~~~
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tensorflow-gpu 1.15 nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 True
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tensorflow-gpu 1.15 nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 False
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tensorflow-gpu 1.15 nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04 False
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tensorflow-gpu 1.15 nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04 False
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tensorflow-gpu 1.15 nvidia/cuda:11.1-cudnn8-runtime-ubuntu18.04 False
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tensorflow-gpu 1.15 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04 False
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tensorflow 2.4.3 nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.4.3 nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.4.3 nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.4.3 nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04 True
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tensorflow 2.4.3 nvidia/cuda:11.1-cudnn8-runtime-ubuntu18.04 False
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tensorflow 2.4.3 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04 False
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tensorflow 2.5.1 nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.5.1 nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.5.1 nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.5.1 nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04 False
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tensorflow 2.5.1 nvidia/cuda:11.1-cudnn8-runtime-ubuntu18.04 True
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tensorflow 2.5.1 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04 True
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tensorflow 2.6.0 nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.6.0 nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.6.0 nvidia/cuda:10.2-cudnn7-runtime-ubuntu18.04 False
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tensorflow 2.6.0 nvidia/cuda:11.0-cudnn8-runtime-ubuntu18.04 False
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tensorflow 2.6.0 nvidia/cuda:11.1-cudnn8-runtime-ubuntu18.04 True
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tensorflow 2.6.0 nvidia/cuda:11.2.1-cudnn8-runtime-ubuntu18.04 True
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~~~
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