Python deeplabcut卡在启动训练中

由于cuda/nvidia/tf的问题，我放弃在ubuntu 20.04中运行DLC后，我尝试在windows 10机器上运行DLC。该卡是RTX2080

sess=tf.Session（config=tf.ConfigProto（log\u device\u placement=True））

输出

2020-11-15 18:11:03.796432: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2020-11-15 18:11:03.919320: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce RTX 2080 SUPER major: 7 minor: 5 memoryClockRate(GHz): 1.815
pciBusID: 0000:01:00.0
totalMemory: 8.00GiB freeMemory: 6.55GiB
2020-11-15 18:11:03.922455: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2020-11-15 18:11:04.214684: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-15 18:11:04.216502: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2020-11-15 18:11:04.217638: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2020-11-15 18:11:04.218748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6279 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 SUPER, pci bus id: 0000:01:00.0, compute capability: 7.5)
Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce RTX 2080 SUPER, pci bus id: 0000:01:00.0, compute capability: 7.5
2020-11-15 18:11:04.224196: I tensorflow/core/common_runtime/direct_session.cc:317] Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce RTX 2080 SUPER, pci bus id: 0000:01:00.0, compute capability: 7.5

然后：

产出：

[[22. 28.]
 [49. 64.]]

所以我猜gpu的配置是正确的

我以管理员身份运行anaconda提示符

当培训开始时，我可以看到gpu内存使用量跃升到6gb。你知道为什么这样不行吗

[[22. 28.]
 [49. 64.]]