Unable to install the requirements
See original GitHub issueHello,
I have installed Sockeye in an Anaconda (Conda 4.10.3 with Python 3.8.8) environment as explained here: https://awslabs.github.io/sockeye/setup.html
But I can’t install mxnet:
Could not find a version that satisfies the requirement mxnet==1.8.0.post0
I tried it with conda install -c anaconda mxnet and with pip install mxnet==1.8.0.post0,
but nothing could help.
Do you know why I can’t install mxnet?
I want to train the model described here: https://aws.amazon.com/blogs/machine-learning/train-neural-machine-translation-models-with-sockeye/
Issue Analytics
- State:
- Created 2 years ago
- Comments:39 (19 by maintainers)
Top Results From Across the Web
pip fails to install packages from requirements.txt
It looks like the numexpr package has an install-time dependency on numpy. Pip makes two passes through your requirements: first it ...
Read more >pip install -r requirements.txt fails · Issue #3 · deepmind/dqn_zoo
I created a new virtual environment and immediately tried to install the requirements, but ran into a version error: pip install -r ...
Read more >Getting Error while running pip install -r requirements.txt after ...
The course has been tested with Python 3.8 and this error usually happens when using an earlier/later version since the package gets deprecated ......
Read more >"Can't install. An error occurred, although your system meets ...
During Custom Install or Online Deployment process this error appears: "Can't ... An error occurred, although your system meets requirements.
Read more >Could not find a version that satisfies the requirement X
The error "Could not find a version that satisfies the requirement" is commonly caused when we try to pip install a built-in Python...
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found

Ok, then I think your only choice is to work within the WSL and install Mxnet 1.8.0 with support for CUDA 10.1 (https://pypi.org/project/mxnet-cu101/1.8.0.post0/):
Make sure that after installing everything, mxnet-cu101==1.8.0 is exactly what is installed. To check this:
(Technically you could still build mxnet from scratch with different dependencies that match your Windows machine exactly.)
This could mean that CUDA is in fact not installed on your system. (Having
nvidia-smidoes not mean that CUDA is installed.)