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Started by user Jeremy Enos Running as SYSTEM Building in workspace /var/lib/jenkins/jobs/tensorflow/workspace [SSH] script: module load anaconda3_gpu module load cudnn cd python rm -f tensorflow_test.txt srun --nodes=1 --ntasks-per-node=1 --mem=16g \ --time=00:05:00 \ --partition=a100rome \ --account=bbmb-hydro \ --gpus-per-node=1 \ --gpu-bind=closest \ python3 cifar10gpu.py | tee tensorflow_test.txt YVALUE=`grep "wall time seconds" tensorflow_test.txt | cut -d'=' -f2` echo YVALUE=$YVALUE > tensorflow_time.txt [SSH] executing... srun: job 96858 queued and waiting for resources srun: job 96858 has been allocated resources 2024-11-08 03:15:25.873013: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2024-11-08 03:15:26.999418: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2024-11-08 03:15:30.322437: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /sw/spack/hydrogpu-2022-06/apps/cudnn/8.4.0.27-11.6-gcc-11.3.0-qbhsfav/lib:/sw/spack/hydrogpu-2022-06/apps/cuda/11.7.0-gcc-11.3.0-3ysno6b/lib64:/sw/spack/hydrogpu-2022-06/apps/openmpi/4.1.4-gcc-11.3.0-i6koipj/lib:/sw/spack/hydrogpu-2022-06/apps/gcc/11.3.0-gcc-8.4.1-kroofxa/lib64:/sw/spack/hydrogpu-2022-06/apps/gcc/11.3.0-gcc-8.4.1-kroofxa/lib 2024-11-08 03:15:30.323714: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /sw/spack/hydrogpu-2022-06/apps/cudnn/8.4.0.27-11.6-gcc-11.3.0-qbhsfav/lib:/sw/spack/hydrogpu-2022-06/apps/cuda/11.7.0-gcc-11.3.0-3ysno6b/lib64:/sw/spack/hydrogpu-2022-06/apps/openmpi/4.1.4-gcc-11.3.0-i6koipj/lib:/sw/spack/hydrogpu-2022-06/apps/gcc/11.3.0-gcc-8.4.1-kroofxa/lib64:/sw/spack/hydrogpu-2022-06/apps/gcc/11.3.0-gcc-8.4.1-kroofxa/lib 2024-11-08 03:15:30.323726: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. 2024-11-08 03:15:37.938167: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2024-11-08 03:15:39.263878: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 79148 MB memory: -> device: 0, name: NVIDIA A100 80GB PCIe, pci bus id: 0000:21:00.0, compute capability: 8.0 (50000, 32, 32, 3) (10000, 32, 32, 3) Epoch 1/10 2024-11-08 03:15:43.113121: I tensorflow/stream_executor/cuda/cuda_blas.cc:1614] TensorFloat-32 will be used for the matrix multiplication. 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ETA: 0s - loss: 1.3160 - accuracy: 0.5371 1408/1563 [==========================>...] - ETA: 0s - loss: 1.3166 - accuracy: 0.5367 1442/1563 [==========================>...] - ETA: 0s - loss: 1.3171 - accuracy: 0.5368 1476/1563 [===========================>..] - ETA: 0s - loss: 1.3166 - accuracy: 0.5369 1510/1563 [===========================>..] - ETA: 0s - loss: 1.3173 - accuracy: 0.5365 1543/1563 [============================>.] - ETA: 0s - loss: 1.3178 - accuracy: 0.5363 1563/1563 [==============================] - 2s 2ms/step - loss: 1.3174 - accuracy: 0.5367 Epoch 9/10 1/1563 [..............................] - ETA: 2s - loss: 1.5759 - accuracy: 0.5000 35/1563 [..............................] - ETA: 2s - loss: 1.2615 - accuracy: 0.5625 69/1563 [>.............................] - ETA: 2s - loss: 1.2823 - accuracy: 0.5543 103/1563 [>.............................] - ETA: 2s - loss: 1.2834 - accuracy: 0.5455 138/1563 [=>............................] - ETA: 2s - loss: 1.2840 - accuracy: 0.5505 172/1563 [==>...........................] - 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ETA: 0s - loss: 1.2529 - accuracy: 0.5591 1050/1563 [===================>..........] - ETA: 0s - loss: 1.2535 - accuracy: 0.5590 1084/1563 [===================>..........] - ETA: 0s - loss: 1.2533 - accuracy: 0.5589 1118/1563 [====================>.........] - ETA: 0s - loss: 1.2526 - accuracy: 0.5588 1152/1563 [=====================>........] - ETA: 0s - loss: 1.2528 - accuracy: 0.5588 1186/1563 [=====================>........] - ETA: 0s - loss: 1.2531 - accuracy: 0.5590 1220/1563 [======================>.......] - ETA: 0s - loss: 1.2547 - accuracy: 0.5583 1254/1563 [=======================>......] - ETA: 0s - loss: 1.2548 - accuracy: 0.5581 1289/1563 [=======================>......] - ETA: 0s - loss: 1.2538 - accuracy: 0.5585 1323/1563 [========================>.....] - ETA: 0s - loss: 1.2528 - accuracy: 0.5588 1357/1563 [=========================>....] - ETA: 0s - loss: 1.2522 - accuracy: 0.5590 1391/1563 [=========================>....] - ETA: 0s - loss: 1.2526 - accuracy: 0.5589 1426/1563 [==========================>...] - ETA: 0s - loss: 1.2528 - accuracy: 0.5589 1460/1563 [===========================>..] - ETA: 0s - loss: 1.2531 - accuracy: 0.5588 1494/1563 [===========================>..] - ETA: 0s - loss: 1.2528 - accuracy: 0.5590 1528/1563 [============================>.] - ETA: 0s - loss: 1.2532 - accuracy: 0.5588 1562/1563 [============================>.] - ETA: 0s - loss: 1.2542 - accuracy: 0.5583 1563/1563 [==============================] - 2s 1ms/step - loss: 1.2543 - accuracy: 0.5582 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= flatten (Flatten) (None, 3072) 0 dense (Dense) (None, 3000) 9219000 dense_1 (Dense) (None, 1000) 3001000 dense_2 (Dense) (None, 10) 10010 ================================================================= Total params: 12,230,010 Trainable params: 12,230,010 Non-trainable params: 0 _________________________________________________________________ None wall time seconds (without loading test data set)= 29.74904990196228 hydro06 [SSH] completed [SSH] exit-status: 0 [workspace] $ /bin/sh -xe /tmp/jenkins7353026830000382610.sh + scp 'HYDRO_REMOTE:~svchydrojenkins/python/tensorflow_time.txt' /var/lib/jenkins/jobs/tensorflow/workspace Recording plot data Saving plot series data from: /var/lib/jenkins/jobs/tensorflow/workspace/tensorflow_time.txt Sending e-mails to: [email protected] Finished: SUCCESS