I’m getting the printout below when running a PyTorch training loop. Is there anything that I should do to configure the instance? It states I may get lower performance, I’m not sure if that is the case though when using PyTorch.
2023-06-26 21:25:08.743143: 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: AVX512F AVX512_VNNI AVX512_BF16 AVX_VNNI
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-06-26 21:25:08.904188: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variableTF_ENABLE_ONEDNN_OPTS=0
.WARNING: No preset parameters were found for the device that Open MPI
detected:Local host: 209-20-157-229
Device name: mlx5_0
Device vendor ID: 0x02c9
Device vendor part ID: 4122Default device parameters will be used, which may result in lower
performance. You can edit any of the files specified by the
btl_openib_device_param_files MCA parameter to set values for your
device.NOTE: You can turn off this warning by setting the MCA parameter
btl_openib_warn_no_device_params_found to 0.
No OpenFabrics connection schemes reported that they were able to be
used on a specific port. As such, the openib BTL (OpenFabrics
support) will be disabled for this port.Local host: 209-20-157-229
Local device: mlx5_0
Local port: 1
CPCs attempted: udcm