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 96605 queued and waiting for resources
srun: job 96605 has been allocated resources
2024-11-04 07:43:06.011271: 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.
2024-11-04 07:43:30.281203: 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
2024-11-04 07:44:04.801714: 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
2024-11-04 07:44:04.802463: 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
2024-11-04 07:44:04.802472: 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.
2024-11-04 07:45:00.003243: 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.
2024-11-04 07:45:02.402105: 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
2024-11-04 07:45:09.873090: I tensorflow/stream_executor/cuda/cuda_blas.cc:1614] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
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1563/1563 [==============================] - 6s 2ms/step - loss: 1.8079 - accuracy: 0.3563
Epoch 2/10
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Epoch 3/10
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Epoch 4/10
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Epoch 5/10
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Epoch 6/10
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Epoch 7/10
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Epoch 8/10
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Epoch 9/10
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Epoch 10/10
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916/1563 [================>.............] - ETA: 1s - loss: 1.2604 - accuracy: 0.5570
949/1563 [=================>............] - ETA: 0s - loss: 1.2609 - accuracy: 0.5565
982/1563 [=================>............] - ETA: 0s - loss: 1.2600 - accuracy: 0.5564
1015/1563 [==================>...........] - ETA: 0s - loss: 1.2577 - accuracy: 0.5573
1049/1563 [===================>..........] - ETA: 0s - loss: 1.2578 - accuracy: 0.5578
1082/1563 [===================>..........] - ETA: 0s - loss: 1.2554 - accuracy: 0.5580
1115/1563 [====================>.........] - ETA: 0s - loss: 1.2550 - accuracy: 0.5578
1148/1563 [=====================>........] - ETA: 0s - loss: 1.2550 - accuracy: 0.5577
1182/1563 [=====================>........] - ETA: 0s - loss: 1.2538 - accuracy: 0.5580
1215/1563 [======================>.......] - ETA: 0s - loss: 1.2522 - accuracy: 0.5584
1248/1563 [======================>.......] - ETA: 0s - loss: 1.2523 - accuracy: 0.5586
1281/1563 [=======================>......] - ETA: 0s - loss: 1.2519 - accuracy: 0.5589
1314/1563 [========================>.....] - ETA: 0s - loss: 1.2522 - accuracy: 0.5592
1347/1563 [========================>.....] - ETA: 0s - loss: 1.2516 - accuracy: 0.5591
1380/1563 [=========================>....] - ETA: 0s - loss: 1.2529 - accuracy: 0.5586
1413/1563 [==========================>...] - ETA: 0s - loss: 1.2529 - accuracy: 0.5586
1447/1563 [==========================>...] - ETA: 0s - loss: 1.2541 - accuracy: 0.5582
1480/1563 [===========================>..] - ETA: 0s - loss: 1.2535 - accuracy: 0.5589
1515/1563 [============================>.] - ETA: 0s - loss: 1.2534 - accuracy: 0.5593
1549/1563 [============================>.] - ETA: 0s - loss: 1.2537 - accuracy: 0.5594
1563/1563 [==============================] - 2s 2ms/step - loss: 1.2544 - accuracy: 0.5592
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)= 40.19088649749756
hydro05
[SSH] completed
[SSH] exit-status: 0
[workspace] $ /bin/sh -xe /tmp/jenkins11280433193546265165.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
![[Jenkins]](/static/755cd4af/images/svgs/logo.svg){kind=logo}
