Closed timm closed 5 years ago
Hello,
We have run the software on linux (Ubuntu 16.04.1 LTS) only, Windows might be an issue, this specific version of tensorflow-gpu might not be available on that platform.
We used CUDA 9.0 and cudNN 7.1.4.
You can try to use tensorflow instead of tensorflow-gpu. This should make it easier to verify that the software is working.
Alternatively, you can also use Theano==1.0.2 instead of tensorflow and create/alter the keras configuration file, which usually is located at HOME_DIRECTORY/.keras/keras.json:
{ "floatx": "float32", "epsilon": 1e-07, "backend": "theano", "image_data_format": "channels_last" }
We will adjust the documentation accordingly.
Dear Authors,
Thanks for the update. I am able to run the project using Theano
as backend.
Upon a thorough investigation, I found the following issues which are mostly related to documentation:
conf\pvm-multi-pretrained.json
has a comma
missing, preventing project execution due to parsing error. Formal_verification
, Process_audit
etc.As for a badge, since a publicly accessible DOI link has been provided for the artifacts and considering the above points will be addressed, I recommend a badge of Available
.
hi @artifact-review can you please clarify - the badge is recommended upon fixing the documentation? or independently?
@neilernst I recommend the badge of "Available" irrespective of the documentation fixes. Sorry for the confusion.
thanks - @andivogelsang suggest when possible you make these changes anyway, as it will probably help you just as much :)
@timm please concur on this badge or comment with other changes
Hi, We tried to create a virtual environment for Python 3.6 as per specified in requirements.txt. However, we have encountered a number of issues in doing so as listed out below:
We used the following command to install all the dependencies
pip3 install -r requirements.txt
. Unfortunately, it could never resolve the version of 1.10.1 for the tensorflow-gpu library. The error message reads:Could not find a version that satisfies the requirement tensorflow-gpu==1.10.1
Then, we tried to create an environment taking the latest version of everything. Unfortunately, it was never successful. Probably, for mismatching installation of deep learning libraries (CUDA, cuDNN, etc.). So, please specify which version of CUDA toolkit and cuDNN library needs to be installed for the desired environment.
The configuration of the machine from which we're trying to launch this project is as follows: