Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

TensorFlow2.0的速度比pytorch更好 #20

Closed
l976308589 opened this issue Nov 19, 2019 · 5 comments
Closed

TensorFlow2.0的速度比pytorch更好 #20

l976308589 opened this issue Nov 19, 2019 · 5 comments
Labels
contributor

Comments

@l976308589
Copy link

您好，建议您在0.4版本中使用TensorFlow2.0
其接口做了优化，速度也会提升
@guofei9987
Copy link
Owner

感谢建议！目前仍在这几个架构中做取舍。发布版本会综合考虑性能、稳定性和可扩展性。

@l976308589
Copy link
Author

应该是感谢您分享如此优秀的项目
我使用cupy+jax复写过您部分代码

@json007
Copy link

json007 commented Dec 4, 2019

应该是感谢您分享如此优秀的项目
我使用cupy+jax复写过您部分代码

有个疑问，既然都用了cupy +jax,为啥不选择pytorch, 既有jit, Autograd, 也支持GPU，包含AMD的ROCm

@l976308589
Copy link
Author

应该是感谢您分享如此优秀的项目
我使用cupy+jax复写过您部分代码

有个疑问，既然都用了cupy +jax,为啥不选择pytorch, 既有jit, Autograd, 也支持GPU，包含AMD的ROCm

因为pytorch部署远不如tf2

@guofei9987
Copy link
Owner

应该是感谢您分享如此优秀的项目
我使用cupy+jax复写过您部分代码

有个疑问，既然都用了cupy +jax,为啥不选择pytorch, 既有jit, Autograd, 也支持GPU，包含AMD的ROCm

因为pytorch部署远不如tf2

是这样的

guofei9987 added a commit that referenced this issue Dec 11, 2019
@guofei9987
News about issue #20, working on it.
b6cb896
guofei9987 added a commit that referenced this issue Jan 10, 2020
@guofei9987
Use Pytorch to do GPU computation #20
ffe5031
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
contributor
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
3 participants
@json007 @l976308589 @guofei9987