I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:150] kernel reported version is: 352.93 I tensorflow/core/common_runtime/gpu/gpu_init.cc:81] No GPU devices available on machine. tensorflow cannot access GPU in Docker RuntimeError: cuda runtime error (100) : no CUDA-capable device is ...
/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fall...
E tensorflow/stream_executor/cuda/cuda_diagnostics.cc:296] kernel version 367.48.0 does not match DSO version 367.57.0 — cannot find working devices in this configuration I tensorflow/core/common_runtime/gpu/gpu_init.cc:81] No GPU devices available on machine. Reply muralli mallika...
'kernel_h': 3, 'kernel_w': 3, 'checkpoint': None, 'checkpoint_dir': '/content/downloads/waveflow_res128_ljspeech_ckpt_1.0', 'iteration': None, 'name': '', 'output': './syn_audios', 'sample': 0, 'use_fp16': True, 'use_gpu': True} /usr/local/lib/python3.6/dist-package...
My k8s version isv1.9.5and I use Nvidia GPU in container via setting--feature-aget=Accelerators=truein kubelet instead ofdevice-plugin, It does work when running tensorflow with GPU in container. I checkNot able to collect metrics for nvidia GPUwhere@mindprinceclaimed that ...