ML引擎批处理预测在错误的python版本上运行

ML引擎批处理预测在错误的python版本上运行,python,tensorflow,google-cloud-platform,google-cloud-ml,Python,Tensorflow,Google Cloud Platform,Google Cloud Ml,因此,我有一个python 3.5中的tensorflow模型在ML引擎中注册,我想使用它运行一个批处理预测作业。我的API请求正文如下所示: { "versionName": "XXXXX/v8_0QSZ", "dataFormat": "JSON", "inputPaths": [ "XXXXX" ], "outputPath": "XXXXXX", "region": "us-east1", "runtimeVersion": "1.12", "ac

因此,我有一个python 3.5中的tensorflow模型在ML引擎中注册,我想使用它运行一个批处理预测作业。我的API请求正文如下所示:

{
  "versionName": "XXXXX/v8_0QSZ",
  "dataFormat": "JSON",
  "inputPaths": [
    "XXXXX"
  ],
  "outputPath": "XXXXXX",
  "region": "us-east1",
  "runtimeVersion": "1.12",
  "accelerator": {
    "count": "1",
    "type": "NVIDIA_TESLA_P100"
  }
}
然后,批处理预测作业运行并返回“作业已成功完成”。但是,它完全不成功,并始终为每个输入抛出以下错误:

Exception during running the graph: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[node convolution_layer/conv1d/conv1d/Conv2D (defined at /usr/local/lib/python2.7/dist-packages/google/cloud/ml/prediction/frameworks/tf_prediction_lib.py:210) = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](convolution_layer/conv1d/conv1d/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer, convolution_layer/conv1d/conv1d/ExpandDims_1)]] [[{{node Cast_6/_495}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_789_Cast_6", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]] 
我的问题是:

  • 为什么批处理作业报告成功,而实际上它完全失败了
  • 在上面的异常中,它提到了Python2.7。。。然而,该模型注册为Python3.5,无法使用API指定python版本。为什么批量预测使用2.7
  • 一般来说,我能做些什么来实现这一点
  • 这与我的加速器选项有关吗
      来自批处理预测开发人员的响应:“我们还没有正式支持Python 3。但是,您遇到的问题是一个影响TF 1.11和1.12的GPU运行时的已知错误。”来自批处理预测开发人员的响应:“我们还没有正式支持Python 3。然而,您遇到的问题是一个影响TF 1.11和1.12的GPU运行时的已知错误“您能否将之前的评论作为答案发布。这将使社区更了解此信息。