INFO: underlay of /etc/localtime required more than 50 (88) bind mounts INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts 2023-07-14 16:01:07.453762: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 16:01:09.815807: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2023-07-14 16:01:09.819951: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1 2023-07-14 16:01:10.782100: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: pciBusID: 0000:0a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0 coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s 2023-07-14 16:01:10.782202: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 16:01:10.804049: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11 2023-07-14 16:01:10.804105: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11 2023-07-14 16:01:10.813648: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10 2023-07-14 16:01:10.818300: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10 2023-07-14 16:01:10.834024: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10 2023-07-14 16:01:10.838238: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11 2023-07-14 16:01:10.839147: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8 2023-07-14 16:01:10.869123: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0 2023-07-14 16:01:10.869593: I tensorflow/core/platform/cpu_feature_guard.cc:142] 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. 2023-07-14 16:01:10.871045: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set 2023-07-14 16:01:10.889479: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: pciBusID: 0000:0a:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0 coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s 2023-07-14 16:01:10.889540: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 16:01:10.889578: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11 2023-07-14 16:01:10.889607: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11 2023-07-14 16:01:10.889633: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10 2023-07-14 16:01:10.889658: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10 2023-07-14 16:01:10.889683: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10 2023-07-14 16:01:10.889708: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11 2023-07-14 16:01:10.889752: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8 2023-07-14 16:01:10.931485: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0 2023-07-14 16:01:10.933916: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 2023-07-14 16:01:13.217922: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix: 2023-07-14 16:01:13.217984: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0 2023-07-14 16:01:13.217996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N 2023-07-14 16:01:13.302069: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:0a:00.0, compute capability: 8.0) 2023-07-14 16:01:15.379998: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them. /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors. , UserWarning)