TensorFlow 2.4.0 的确切 CUDA / cudNN 版本

Question

我正在尝试将Anaconda3（2020.11与Python 3.8.5 64-BIT）与ZCB20B20B802A3F0255E05E05E054E ESTICE ONTERIPENT SYAPER SYAPER SYAPER SEAL ESTEBINE ON ZAAEAEASAPY ON ION 4BB IN BY 334 ESB.234ENEM 43.4888888888888888888.BENTIM 30BENTIM 3YNEBY HENGES ON TORING YESTAP

真正令人费解的是，每个库都依赖于另一个库的确切版本，而不是更多，而不是更少！

到目前为止，我设法安装：

• Anaconda3（2020.11 与 Python 3.8.5 64 位）
• tensorflow 2.4.0
• CUDA 11.0.2，仅运行时，使用网络安装程序
• cudnn-11.0-windows-x64-v8.0.4.30
• GeForce 驱动程序 461.09-desktop-win10-64bit-international-dch-whql
• 主板是 Geforce RTX 3070

根据手册https://www.tensorflow.org/install/gpu应该没问题，但不幸的是，我仍然收到可怕的"Error retrieving driver version: Unimplemented: kernel reported driver version not implemented on Windows"消息。

这是完整的跟踪：

2021-01-20 20:53:25.785203: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-20 20:53:29.173495: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-20 20:53:29.175299: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-01-20 20:53:29.213308: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-20 20:53:29.213536: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-20 20:53:29.237764: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-20 20:53:29.237865: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-20 20:53:29.244635: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-20 20:53:29.247913: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-20 20:53:29.262791: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-20 20:53:29.268091: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-20 20:53:29.278049: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-20 20:53:29.278203: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-20 20:53:29.279054: 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
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-01-20 20:53:29.281144: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.755GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-20 20:53:29.281321: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-01-20 20:53:29.281786: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-20 20:53:29.282156: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-20 20:53:29.282961: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-01-20 20:53:29.283385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-01-20 20:53:29.284167: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-01-20 20:53:29.284635: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-01-20 20:53:29.286872: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-20 20:53:29.289197: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-01-20 20:53:29.772262: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-20 20:53:29.772375: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-01-20 20:53:29.773599: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-01-20 20:53:29.774277: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-20 20:53:29.775166: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-20 20:53:30.414473: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-20 20:53:31.860756: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-01-20 20:53:32.450199: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-01-20 20:53:32.476605: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-01-20 20:53:33.172408: E tensorflow/stream_executor/cuda/cuda_dnn.cc:336] Could not create cudnn handle: CUDNN_STATUS_NOT_INITIALIZED
2021-01-20 20:53:33.172484: E tensorflow/stream_executor/cuda/cuda_dnn.cc:340] Error retrieving driver version: Unimplemented: kernel reported driver version not implemented on Windows

从文档来看，这可能与使用错误的库组合有关，但我真的不知道：我可能正在做任何测试来解决这个问题？

Answer 1

我认为问题在于 GeForce 驱动程序 461.09-desktop-win10-64bit-international-dch-whql。 它包括 CUDA 11.2，而不是 11。我想您需要找到与您的卡兼容的 GeForce 驱动程序版本，其中包括 CUDA 11。看起来版本 450.36.06+ 可以为您工作。 我建议您从计算机中卸载 CUDA 11.2 和当前驱动程序并安装旧版本。