win10 无法运行

[xunchang521]

ERROR: Command errored out with exit status 1: command: 'C:\Users\Shinelon\AppData\Local\Programs\Python\Python36\python.exe' -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\Shinelon\AppData\Local\Temp\pip-install-dwbkvitr\backports-datetime-fromisoformat_cf6614884905473692fac77a541575f6\setup.py'"'"'; file='"'"'C:\Users\Shinelon\AppData\Local\Temp\pip-install-dwbkvitr\backports-datetime-fromisoformat_cf6614884905473692fac77a541575f6\setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(file) if os.path.exists(file) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\Shinelon\AppData\Local\Temp\pip-wheel-7d5kqunx' cwd: C:\Users\Shinelon\AppData\Local\Temp\pip-install-dwbkvitr\backports-datetime-fromisoformat_cf6614884905473692fac77a541575f6
Complete output (12 lines): running bdist_wheel running build running build_py creating build creating build\lib.win-amd64-3.6 creating build\lib.win-amd64-3.6\backports copying backports_init_.py -> build\lib.win-amd64-3.6\backports creating build\lib.win-amd64-3.6\backports\datetime_fromisoformat copying backports\datetime_fromisoformat_init_.py -> build\lib.win-amd64-3.6\backports\datetime_fromisoformat running build_ext building 'backports._datetime_fromisoformat' extension error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/

ERROR: Failed building wheel for backports-datetime-fromisoformat

[xunchang521]

python 3.6 不行是吧

[infstellar]

应该是没装C++运行时吧 error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/

[xunchang521]

现在有个问题我的gpu显存一直爆满，训练数据怎么改大小？？

[xunchang521]

2 root error(s) found. (0) Resource exhausted: failed to allocate memory [[{{node loss_1/time_distributed_3_loss/mul}}]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

 [[loss_1/mul/_187]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

(1) Resource exhausted: failed to allocate memory [[{{node loss_1/time_distributed_3_loss/mul}}]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

0 successful operations. 0 derived errors ignored.