在R-无效版本规范中安装Keras GPU时出错

Question

我遵循了许多指南，尝试在我的新笔记本上安装带有GPU的Keras。一些细节：

• Windows 10 64位
• Nvidia T1000 GPU
• R版本4.0.4
• 我跟踪了这的软件依赖关系，包括CUDA11.2和cuDNN 8.1.1。基于cuDNN站点，这是数据自动化系统11.2的正确cuDNN。我还更新了司机的信息。
• 我在NVIDIA计算工具包中将cuDNN文件从bin、include和lib复制到各自的文件夹中。
• 我还将这些文件夹和cuDNN文件夹添加到PATH环境变量中。

以下是我的CUDA bin文件夹中的文件(我尝试过安装CUDA 10、10.1和11.2)：

list.files("C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v11.2\\bin\\")
 [1] "bin2c.exe"                "compute-sanitizer.bat"    "crt"                      "cu++filt.exe"            
 [5] "cublas64_10.dll"          "cublas64_100.dll"         "cublas64_11.dll"          "cublasLt64_10.dll"       
 [9] "cublasLt64_11.dll"        "cuda-memcheck.exe"        "cudafe++.exe"             "cudart32_110.dll"        
[13] "cudart64_100.dll"         "cudart64_101.dll"         "cudart64_110.dll"         "cudnn_adv_infer64_8.dll" 
[17] "cudnn_adv_train64_8.dll"  "cudnn_cnn_infer64_8.dll"  "cudnn_cnn_train64_8.dll"  "cudnn_ops_infer64_8.dll" 
[21] "cudnn_ops_train64_8.dll"  "cudnn64_8.dll"            "cufft64_10.dll"           "cufftw64_10.dll"         
[25] "cuinj64_112.dll"          "cuobjdump.exe"            "curand64_10.dll"          "cusolver64_10.dll"       
[29] "cusolverMg64_11.dll"      "cusparse64_10.dll"        "cusparse64_11.dll"        "fatbinary.exe"           
[33] "nppc64_11.dll"            "nppial64_11.dll"          "nppicc64_11.dll"          "nppidei64_11.dll"        
[37] "nppif64_11.dll"           "nppig64_11.dll"           "nppim64_11.dll"           "nppist64_11.dll"         
[41] "nppisu64_11.dll"          "nppitc64_11.dll"          "npps64_11.dll"            "nvblas64_11.dll"         
[45] "nvcc.exe"                 "nvcc.profile"             "nvdisasm.exe"             "nvjpeg64_11.dll"         
[49] "nvlink.exe"               "nvprof.exe"               "nvprune.exe"              "nvrtc-builtins64_112.dll"
[53] "nvrtc-prev"               "nvrtc64_112_0.dll"        "nvvp.bat"                 "ptxas.exe"    

我试过引导这里、这里和这里。

我成功地跑了：

tensorflow::install_tensorflow(gpu = TRUE)
reticulate::use_condaenv("r-tensorflow")
tf$constant("hello")

然后我收到消息：

2021-03-08 20:54:50.917771: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-03-08 20:55:00.607511: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-03-08 20:55:02.286421: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: Quadro T1000 computeCapability: 7.5
coreClock: 1.53GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2021-03-08 20:55:02.286702: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-03-08 20:55:02.657731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-03-08 20:55:03.052477: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-03-08 20:55:03.230033: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-03-08 20:55:03.526342: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 20:55:03.920362: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-03-08 20:55:03.930081: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-03-08 20:55:04.440275: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-03-08 20:55:04.440969: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2021-03-08 20:55:04.450175: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x211965ca050 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-03-08 20:55:04.450424: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2021-03-08 20:55:04.450851: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: Quadro T1000 computeCapability: 7.5
coreClock: 1.53GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2021-03-08 20:55:04.451300: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-03-08 20:55:04.451552: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-03-08 20:55:04.451803: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-03-08 20:55:04.451982: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-03-08 20:55:04.452149: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 20:55:04.452363: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-03-08 20:55:04.452502: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-03-08 20:55:04.452708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-03-08 20:55:05.372995: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-08 20:55:05.373218: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2021-03-08 20:55:05.373358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2021-03-08 20:55:05.373600: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2917 MB memory) -> physical GPU (device: 0, name: Quadro T1000, pci bus id: 0000:01:00.0, compute capability: 7.5)
2021-03-08 20:55:05.376339: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x211965dcad0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-03-08 20:55:05.376629: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Quadro T1000, Compute Capability 7.5
tf.Tensor(b'hello', shape=(), dtype=string)

但是，如果我试着

keras::install_keras(tensorflow = "gpu")

在新的RStudio会话中，我得到

Error: invalid version specification

但随后我尝试从命令行运行conda install -c anaconda keras-gpu，并安装了OK。如果我使用IMDB数据集在Keras上运行测试，那么它似乎运行得很好：

library(keras)
model <- keras_model_sequential() %>% 
  layer_dense(units = 16, activation = "relu", input_shape = c(10000)) %>% 
  layer_dense(units = 16, activation = "relu") %>% 
  layer_dense(units = 1, activation = "sigmoid")

返回：

2021-03-08 21:51:14.726620: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-03-08 21:51:16.456659: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: Quadro T1000 computeCapability: 7.5
coreClock: 1.53GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2021-03-08 21:51:16.456844: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-03-08 21:51:16.460816: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-03-08 21:51:16.465207: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-03-08 21:51:16.466657: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-03-08 21:51:16.470899: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 21:51:16.473512: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-03-08 21:51:16.482108: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-03-08 21:51:16.482375: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-03-08 21:51:16.484124: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2021-03-08 21:51:16.495226: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1edbf69c2d0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-03-08 21:51:16.495403: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2021-03-08 21:51:16.495774: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: Quadro T1000 computeCapability: 7.5
coreClock: 1.53GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2021-03-08 21:51:16.496029: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-03-08 21:51:16.496131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-03-08 21:51:16.496247: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-03-08 21:51:16.496347: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-03-08 21:51:16.496438: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 21:51:16.496540: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-03-08 21:51:16.496703: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-03-08 21:51:16.496866: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-03-08 21:51:17.007480: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-08 21:51:17.007586: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2021-03-08 21:51:17.007676: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2021-03-08 21:51:17.007896: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2917 MB memory) -> physical GPU (device: 0, name: Quadro T1000, pci bus id: 0000:01:00.0, compute capability: 7.5)
2021-03-08 21:51:17.011318: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1edbf6afdd0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-03-08 21:51:17.011464: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Quadro T1000, Compute Capability 7.5

任何帮助都非常感谢:upside_down_face：

Answer 1

我认为问题在最新的R方案中。我通过使用

require(devtools)
install_version("keras", version = "2.3.0.0")

然后就可以正确安装keras了。