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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 16:57:57.619372: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2023-07-14 16:57:59.915473: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2023-07-14 16:57:59.918816: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2023-07-14 16:58:00.414649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
2023-07-14 16:58:00.414753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2023-07-14 16:58:00.439493: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2023-07-14 16:58:00.439550: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2023-07-14 16:58:00.448761: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2023-07-14 16:58:00.453198: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2023-07-14 16:58:00.468592: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2023-07-14 16:58:00.472736: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2023-07-14 16:58:00.473617: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2023-07-14 16:58:00.505992: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2023-07-14 16:58:00.506458: 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 16:58:00.508051: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2023-07-14 16:58:00.533964: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:84:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
2023-07-14 16:58:00.534025: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2023-07-14 16:58:00.534063: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2023-07-14 16:58:00.534094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2023-07-14 16:58:00.534120: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2023-07-14 16:58:00.534145: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2023-07-14 16:58:00.534170: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2023-07-14 16:58:00.534194: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2023-07-14 16:58:00.534218: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2023-07-14 16:58:00.546155: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2023-07-14 16:58:00.547977: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2023-07-14 16:58:03.687684: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2023-07-14 16:58:03.687800: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2023-07-14 16:58:03.687813: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
2023-07-14 16:58:03.694319: 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: 0000:84:00.0, compute capability: 8.0)
2023-07-14 16:58:05.832362: 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)