Question

我将张量流更新为 2.2.0 并相应地

    nvcc - 11.0
    cudnn - 11.0
    GPU - GTX 1050 ti

运行以下代码时

    print(device_lib.list_local_devices())

我面临以下输出

    [name: "/device:CPU:0"
    device_type: "CPU"
    memory_limit: 268435456
    locality {
    }
    incarnation: 12436950237915670665
    , name: "/device:XLA_CPU:0"
    device_type: "XLA_CPU"
    memory_limit: 17179869184
    locality {
    }
    incarnation: 11900640710651469327
    physical_device_desc: "device: XLA_CPU device"
    , name: "/device:XLA_GPU:0"
    device_type: "XLA_GPU"
    memory_limit: 17179869184
    locality {
    }
    incarnation: 6061376473165052950
    physical_device_desc: "device: XLA_GPU device"
    ]

在任何地方都看不到 gtx 1050ti ，尽管我可以看到设备0提到的GPU，这可能意味着 intel 的内置GPU。

在张量流和Cuda方面， 1050ti 的兼容版本是什么？

更新

我尝试了以下命令

    print(tf.config.list_physical_devices('GPU'))

，结果为空。这是否表示未检测到GPU？

Answer 1

此link提供有关Cuda，tensorflow和Cudnn兼容版本的信息，以检测gpu。对于版本 tensorflow 2.2.0 ， Cudnn7.4 和 Cuda 10.1 ， python 3.8 ，我能够得到以下输出

    [name: "/device:CPU:0"
    device_type: "CPU"
    memory_limit: 268435456
    locality {
    }
    incarnation: 4549764507052008926
    , name: "/device:XLA_CPU:0"
    device_type: "XLA_CPU"
    memory_limit: 17179869184
    locality {
    }
    incarnation: 5130440468361087955
    physical_device_desc: "device: XLA_CPU device"
    , name: "/device:GPU:0"
    device_type: "GPU"
    memory_limit: 3136264601
    locality {
    bus_id: 1
    links {
    }
    }
    incarnation: 8742529146709444949
    physical_device_desc: "device: 0, name: GeForce GTX 1050 Ti, pci bus id: 
    0000:01:00.0, compute capability: 6.1"
    , name: "/device:XLA_GPU:0"
    device_type: "XLA_GPU"
    memory_limit: 17179869184
    locality {
    }
    incarnation: 12774508348529661585
    physical_device_desc: "device: XLA_GPU device"
    ]
    [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

未检测到GPU名称Tensorflow 2.2.0

1 个答案: