Started by timer 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 92231 queued and waiting for resources srun: job 92231 has been allocated resources 2024-10-22 11:53:36.898669: 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. 2024-10-22 11:53:59.846743: 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 2024-10-22 11:54:30.062464: 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 2024-10-22 11:54:30.063138: 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 2024-10-22 11:54:30.063147: 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. 2024-10-22 11:55:13.157772: 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. 2024-10-22 11:55:15.481749: 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 2024-10-22 11:55:22.279664: 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: 1.5436 - accuracy: 0.4560 1563/1563 [==============================] - 2s 2ms/step - loss: 1.5436 - accuracy: 0.4560 Epoch 4/10 1/1563 [..............................] - ETA: 2s - loss: 1.7937 - accuracy: 0.2500 34/1563 [..............................] - ETA: 2s - loss: 1.5453 - accuracy: 0.4586 67/1563 [>.............................] - ETA: 2s - loss: 1.5290 - accuracy: 0.4664 100/1563 [>.............................] - ETA: 2s - loss: 1.5107 - accuracy: 0.4684 133/1563 [=>............................] - ETA: 2s - loss: 1.5085 - accuracy: 0.4716 167/1563 [==>...........................] - ETA: 2s - loss: 1.5021 - accuracy: 0.4740 201/1563 [==>...........................] - ETA: 2s - loss: 1.5015 - accuracy: 0.4754 235/1563 [===>..........................] - ETA: 2s - loss: 1.4924 - accuracy: 0.4785 268/1563 [====>.........................] - ETA: 1s - loss: 1.4947 - accuracy: 0.4782 301/1563 [====>.........................] - ETA: 1s - loss: 1.4964 - accuracy: 0.4779 334/1563 [=====>........................] - 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ETA: 0s - loss: 1.2532 - accuracy: 0.5587 1024/1563 [==================>...........] - ETA: 0s - loss: 1.2535 - accuracy: 0.5586 1057/1563 [===================>..........] - ETA: 0s - loss: 1.2533 - accuracy: 0.5589 1090/1563 [===================>..........] - ETA: 0s - loss: 1.2546 - accuracy: 0.5585 1123/1563 [====================>.........] - ETA: 0s - loss: 1.2535 - accuracy: 0.5587 1156/1563 [=====================>........] - ETA: 0s - loss: 1.2532 - accuracy: 0.5587 1189/1563 [=====================>........] - ETA: 0s - loss: 1.2523 - accuracy: 0.5584 1222/1563 [======================>.......] - ETA: 0s - loss: 1.2542 - accuracy: 0.5582 1255/1563 [=======================>......] - ETA: 0s - loss: 1.2538 - accuracy: 0.5582 1288/1563 [=======================>......] - ETA: 0s - loss: 1.2534 - accuracy: 0.5581 1321/1563 [========================>.....] - ETA: 0s - loss: 1.2541 - accuracy: 0.5576 1354/1563 [========================>.....] - ETA: 0s - loss: 1.2545 - accuracy: 0.5577 1387/1563 [=========================>....] - ETA: 0s - loss: 1.2539 - accuracy: 0.5580 1420/1563 [==========================>...] - ETA: 0s - loss: 1.2541 - accuracy: 0.5579 1453/1563 [==========================>...] - ETA: 0s - loss: 1.2534 - accuracy: 0.5582 1486/1563 [===========================>..] - ETA: 0s - loss: 1.2535 - accuracy: 0.5581 1519/1563 [============================>.] - ETA: 0s - loss: 1.2534 - accuracy: 0.5584 1552/1563 [============================>.] - ETA: 0s - loss: 1.2528 - accuracy: 0.5585 1563/1563 [==============================] - 2s 2ms/step - loss: 1.2532 - accuracy: 0.5584 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)= 38.95181107521057 hydro09 [SSH] completed [SSH] exit-status: 0 [workspace] $ /bin/sh -xe /tmp/jenkins5054386312230774605.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 Finished: SUCCESS