我正在尝试在Azure上构建一个用于模型训练的虚拟机。我找到了这个Data Science Virtual Machine for Linux (Ubuntu)虚拟机，看起来是一个合适的选择。
不幸的是，当我启动虚拟机并安装了caffe的先决条件后，我无法运行测试。在执行make runtest时遇到了以下错误（make all和make test都已无错误完成）：
NVIDIA: no NVIDIA devices foundCuda number of devices: 0Setting to use device 0Current device id: 0Current device name: Note: Randomizing tests' orders with a seed of 97204 .[==========] Running 2041 tests from 267 test cases.[----------] Global test environment set-up.[----------] 11 tests from AdaDeltaSolverTest/3, where TypeParam = caffe::GPUDevice<double>[ RUN ] AdaDeltaSolverTest/3.TestAdaDeltaLeastSquaresUpdateWithHalfMomentumNVIDIA: no NVIDIA devices foundE0715 02:24:32.097311 59355 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.NVIDIA: no NVIDIA devices foundE0715 02:24:32.103780 59355 common.cpp:121] Cannot create Curand generator. Curand won't be available.F0715 02:24:32.103914 59355 test_gradient_based_solver.cpp:80] Check failed: error == cudaSuccess (30 vs. 0) unknown error*** Check failure stack trace: *** @ 0x7f77a463f5cd google::LogMessage::Fail() @ 0x7f77a4641433 google::LogMessage::SendToLog() @ 0x7f77a463f15b google::LogMessage::Flush() @ 0x7f77a4641e1e google::LogMessageFatal::~LogMessageFatal() @ 0x7115e3 caffe::GradientBasedSolverTest<>::TestLeastSquaresUpdate() @ 0x7122af caffe::AdaDeltaSolverTest_TestAdaDeltaLeastSquaresUpdateWithHalfMomentum_Test<>::TestBody() @ 0x8e6023 testing::internal::HandleExceptionsInMethodIfSupported<>() @ 0x8df63a testing::Test::Run() @ 0x8df788 testing::TestInfo::Run() @ 0x8df865 testing::TestCase::Run() @ 0x8e0b3f testing::internal::UnitTestImpl::RunAllTests() @ 0x8e0e63 testing::UnitTest::Run() @ 0x466ecd main @ 0x7f77a111c830 __libc_start_main @ 0x46e589 _start @ (nil) (unknown)Makefile:532: recipe for target 'runtest' failedmake: *** [runtest] Aborted (core dumped)在Azure上是否可以启动一个适合使用caffe进行GPU加速机器学习的虚拟机？
关于虚拟机的所有详细信息请查看这里
回答：
Ubuntu的Data Science Virtual Machine (DSVM)已经在/opt/caffe中安装了Caffe。要在GPU上使用它，请通过选择NC系列之一来创建一个带有K80 GPU的虚拟机。（请确保选择HDD作为存储类型，否则NC系列不会显示。）然后Caffe将可以直接使用。
另外请注意，PyCaffe也是可用的。在终端中执行：
source activate root然后Python将可以使用PyCaffe。
