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 98731 queued and waiting for resources srun: job 98731 has been allocated resources 2024-11-27 07:43:03.348914: 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. 2024-11-27 07:43:04.559269: 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 2024-11-27 07:43:07.544469: 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 2024-11-27 07:43:07.545931: 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 2024-11-27 07:43:07.545939: 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. 2024-11-27 07:43:14.365455: 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. 2024-11-27 07:43:15.131071: 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 2024-11-27 07:43:16.803397: W tensorflow/core/framework/cpu_allocator_impl.cc:82] Allocation of 614400000 exceeds 10% of free system memory. 2024-11-27 07:43:17.180453: W tensorflow/core/framework/cpu_allocator_impl.cc:82] Allocation of 614400000 exceeds 10% of free system memory. (50000, 32, 32, 3) (10000, 32, 32, 3) Epoch 1/10 2024-11-27 07:43:18.569434: 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: 1.4317 - accuracy: 0.4982 1536/1563 [============================>.] - ETA: 0s - loss: 1.4314 - accuracy: 0.4982 1563/1563 [==============================] - 2s 1ms/step - loss: 1.4312 - accuracy: 0.4984 Epoch 6/10 1/1563 [..............................] - ETA: 2s - loss: 1.8477 - accuracy: 0.3125 36/1563 [..............................] - ETA: 2s - loss: 1.4098 - accuracy: 0.5009 71/1563 [>.............................] - ETA: 2s - loss: 1.4013 - accuracy: 0.5092 106/1563 [=>............................] - ETA: 2s - loss: 1.3913 - accuracy: 0.5097 141/1563 [=>............................] - ETA: 2s - loss: 1.3848 - accuracy: 0.5095 176/1563 [==>...........................] - ETA: 2s - loss: 1.3826 - accuracy: 0.5101 211/1563 [===>..........................] - ETA: 1s - loss: 1.3846 - accuracy: 0.5102 246/1563 [===>..........................] - ETA: 1s - loss: 1.3873 - accuracy: 0.5112 281/1563 [====>.........................] - ETA: 1s - loss: 1.3900 - accuracy: 0.5083 316/1563 [=====>........................] - 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2s 1ms/step - loss: 1.3883 - accuracy: 0.5111 Epoch 7/10 1/1563 [..............................] - ETA: 2s - loss: 1.6096 - accuracy: 0.4375 36/1563 [..............................] - ETA: 2s - loss: 1.3739 - accuracy: 0.5139 70/1563 [>.............................] - ETA: 2s - loss: 1.3895 - accuracy: 0.5107 104/1563 [>.............................] - ETA: 2s - loss: 1.3767 - accuracy: 0.5132 139/1563 [=>............................] - ETA: 2s - loss: 1.3871 - accuracy: 0.5112 174/1563 [==>...........................] - ETA: 2s - loss: 1.3752 - accuracy: 0.5165 209/1563 [===>..........................] - ETA: 1s - loss: 1.3667 - accuracy: 0.5200 244/1563 [===>..........................] - ETA: 1s - loss: 1.3634 - accuracy: 0.5197 278/1563 [====>.........................] - ETA: 1s - loss: 1.3588 - accuracy: 0.5201 312/1563 [====>.........................] - ETA: 1s - loss: 1.3604 - accuracy: 0.5205 346/1563 [=====>........................] - ETA: 1s - loss: 1.3521 - accuracy: 0.5240 380/1563 [======>.......................] - 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ETA: 0s - loss: 1.2529 - accuracy: 0.5621 932/1563 [================>.............] - ETA: 0s - loss: 1.2526 - accuracy: 0.5624 967/1563 [=================>............] - ETA: 0s - loss: 1.2518 - accuracy: 0.5628 1002/1563 [==================>...........] - ETA: 0s - loss: 1.2533 - accuracy: 0.5625 1036/1563 [==================>...........] - ETA: 0s - loss: 1.2547 - accuracy: 0.5611 1070/1563 [===================>..........] - ETA: 0s - loss: 1.2568 - accuracy: 0.5605 1105/1563 [====================>.........] - ETA: 0s - loss: 1.2571 - accuracy: 0.5609 1140/1563 [====================>.........] - ETA: 0s - loss: 1.2559 - accuracy: 0.5613 1175/1563 [=====================>........] - ETA: 0s - loss: 1.2560 - accuracy: 0.5614 1209/1563 [======================>.......] - ETA: 0s - loss: 1.2556 - accuracy: 0.5616 1243/1563 [======================>.......] - ETA: 0s - loss: 1.2540 - accuracy: 0.5622 1277/1563 [=======================>......] - ETA: 0s - loss: 1.2550 - accuracy: 0.5615 1312/1563 [========================>.....] - ETA: 0s - loss: 1.2557 - accuracy: 0.5609 1347/1563 [========================>.....] - ETA: 0s - loss: 1.2550 - accuracy: 0.5609 1381/1563 [=========================>....] - ETA: 0s - loss: 1.2547 - accuracy: 0.5607 1416/1563 [==========================>...] - ETA: 0s - loss: 1.2560 - accuracy: 0.5601 1448/1563 [==========================>...] - ETA: 0s - loss: 1.2543 - accuracy: 0.5605 1482/1563 [===========================>..] - ETA: 0s - loss: 1.2536 - accuracy: 0.5606 1516/1563 [============================>.] - ETA: 0s - loss: 1.2537 - accuracy: 0.5605 1551/1563 [============================>.] - ETA: 0s - loss: 1.2540 - accuracy: 0.5601 1563/1563 [==============================] - 2s 1ms/step - loss: 1.2536 - accuracy: 0.5605 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)= 27.75866150856018 hydro03 [SSH] completed [SSH] exit-status: 0 [workspace] $ /bin/sh -xe /tmp/jenkins4790699095174192983.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