我遇到了编译问题。我正在执行的代码来自Udacity的深度学习教程作业4。这使我相信问题不在于代码内，而在于我正在使用的软件工具内。我之前的三个任务没有任何问题，但是现在我正在使用TensorFlow conv2d成员。我的系统详细信息和错误输出在下面列出。任何帮助将不胜感激。如果您需要代码，请告诉我，我将其发布。
系统详情：
- 系统：Windows 10家庭版64位，基于x64的处理器
- CUDA：v 9.0.176
- CUDNN：v 9.0 win10x64 7.3.1.2
- TF-GPU：v 1.5.0通过PIP
- NVIDIA：GTX 1060 6 GiB
- NVIDIA驱动版本：417.35
- python v：3.6.7
输出：
~\Documents\Udacity\Deep Learning\Assignment 4 (CNN's)> python main.py
Training set (200000, 28, 28) (200000,)
Validation set (10000, 28, 28) (10000,)
Test set (10000, 28, 28) (10000,)
Training set (200000, 28, 28, 1) (200000, 10)
Validation set (10000, 28, 28, 1) (10000, 10)
Test set (10000, 28, 28, 1) (10000, 10)
2019-01-04 15:40:09.714793: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2019-01-04 15:40:10.003545: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1105] Found device 0 with properties:
name: GeForce GTX 1060 major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:01:00.0
totalMemory: 6.00GiB freeMemory: 4.97GiB
2019-01-04 15:40:10.013346: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1195] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1060, pci bus
id: 0000:01:00.0, compute capability: 6.1)
Initialized
2019-01-04 15:40:12.584016: E C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_dnn.cc:378] Loaded runtime CuDNN library: 7301 (compatibility version 7300) but source was compiled with 7003 (compatibility version 7000). If using a binary install, upgrade your CuDNN library to match. If building from sources, make sure the library loaded at runtime matches a compatible version specified during compile configuration.
2019-01-04 15:40:12.601433: F C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\kernels\conv_ops.cc:717] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo(), &algorithms)