@@ -27,14 +27,15 @@ In this project, we followed up on the paper by [Paul&Frank(2019)](https://www.a
> *DISCLAIMER :* The problems with the tools described below are not intended to apportion blame or condemnation. The problems we have encountered are simply part of our project process and the reason for our changes and innovations.
As already mentioned we used [this](https://github.com/debjitpaul/Multi-Hop-Knowledge-Paths-Human-Needs) approach provided by @DebjitPaul. Unfortunately, we had some difficulties with the execution of the given code. <br>
Probably the biggest problem was the outdated version information. While we repeatedly encountered the statement to always use the versions of packages that a publisher itself specifies, in this case we were repeatedly confronted with error messages. Every time we worked through an error message and reset versions, we sooner or later came to another error message that another package has a faulty version. <br>
Probably the biggest problem was the outdated version information. While we repeatedly encountered the statement to always use the versions of packages that a publisher himself specifies, in this case we were constantly confronted with error messages. Every time we worked through an error message and reset versions, we sooner or later came to another error message about faulty package version. <br>
In the end, we found that the following complications were to blame: <br>
- the tensorflow version 1.12.0 as recommended in given [github](https://www.aclweb.org/anthology/N19-1368.pdf) does not support tensorflow-hub
- only tensorflow 1.15.0 and upwards supports tensorflow-hub
- python version 3.8 only supports tensorflow versions higher then 2.0
- python version 3.6 was required
- the requirement of kerases was not mentioned anywhere, but is a necessity for the execution of the code
- the requirement of keras was not mentioned anywhere, but is a necessity for the execution of the code
- keras version has to be 2.2.4 because everything higher upgrades tensorflow automatically to tensorflow 2.0
while antyhing lower does not support certain modules needed for the code
- and tensorflow 2.0 has so many technical changes, that it is not compatible with our models
> The final versions that worked for us can be found in README.md
