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Please make sure that this is a build/installation issue. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template
System information
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Win10 pro Visual studio 2015 Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: no TensorFlow installed from (source or binary): trying to build from source TensorFlow version: gpu-1.13.0 Python version: 3.6.7 Installed using virtualenv? pip? conda?: no Bazel version (if compiling from source): 0.21.0 GCC/Compiler version (if compiling from source): CUDA/cuDNN version: CUDA 10.0/ cudnn 7.4.2 GPU model and memory: Geforce 1080Ti Describe the problem I'm trying to build Tensorflow-gpu lib files(tensorflow.dll and .lib files) with bazel from source code on Win10, but I have encountered serveral problems.
Provide the exact sequence of commands / steps that you executed before running into the problem After build configure
C:\tensorflow>python configure.py WARNING: The following rc files are no longer being read, please transfer their contents or import their path into one of the standard rc files: nul WARNING: Running Bazel server needs to be killed, because the startup options are different. WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown". INFO: Invocation ID: 412c8d20-03eb-46e5-bf73-fd54952f1e01 You have bazel 0.21.0 installed. Please specify the location of python. [Default is C:\Users\Administrator\AppData\Local\Programs\Python\Python36\python.exe]:
Found possible Python library paths: C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages Please input the desired Python library path to use. Default is [C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages]
Do you wish to build TensorFlow with XLA JIT support? [y/N]: No XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with ROCm support? [y/N]: No ROCm support will be enabled for TensorFlow.
Do you wish to build TensorFlow with CUDA support? [y/N]: y CUDA support will be enabled for TensorFlow.
Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 10.0]:
Please specify the location where CUDA 10.0 toolkit is installed. Refer to README.md for more details. [Default is C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.0]:
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]:
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.0]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with. You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus. Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 3.5,7.0]:
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is /arch:AVX]:
Would you like to override eigen strong inline for some C++ compilation to reduce the compilation time? [Y/n]: Eigen strong inline overridden.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details. --config=mkl # Build with MKL support. --config=monolithic # Config for mostly static monolithic build. --config=gdr # Build with GDR support. --config=verbs # Build with libverbs support. --config=ngraph # Build with Intel nGraph support. --config=dynamic_kernels # (Experimental) Build kernels into separate shared objects. Preconfigured Bazel build configs to DISABLE default on features: --config=noaws # Disable AWS S3 filesystem support. --config=nogcp # Disable GCP support. --config=nohdfs # Disable HDFS support. --config=noignite # Disable Apacha Ignite support. --config=nokafka # Disable Apache Kafka support. --config=nonccl # Disable NVIDIA NCCL support. I ran
C:\tensorflow>bazel build --config=opt --config=cuda --define=no_tensorflow_py_deps=true //tensorflow/tools/lib_package:libtensorflow Any other info / logs After a long time of compiling, the build did indeed succeed but the lib file it generates is libtensorflow.so
I expect the output lib file for windows to be tensorflow.dll and tensorflow.lib but I think this .so file is not useful on Windows, so I'd like to know:
if I can build a tensorflow.dll and tensorflow.lib file on Win10 or not?
and if not, how do I suppose to use this libtensorflow.so on Windows and deal with all the include file?