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Pytorch Geometric support (deprecates KGCN) #161
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jmsfltchr
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jmsfltchr
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July 19, 2022 18:07
…uild due to tensorflow issue. A previously used patch is no longer applicable to v0.8.0 of rules_python.
…r, split out a separate labeller specifically for the binary link prediction case.
…or binary link prediction
…es (as in the diagnosis example)
…still throws an error
… came from the conversion of a homogeneous graph network into a heterogeneous one. Seemed impossible to debug the call graph creation in pytorch. Now the model runs, but the current issue is getting the model to see the negative samples too. Perhaps a different approach is required (NxN adjacency for the edge concerned).
…roach is easily applicable to predicting all edges in an adjacency matric, as per the link_prediction example.
…tures are given as tensors manually for each node. When given as numpy arrays this way of adding features works fine.
…layer, and now the learner learns with 100% accuracy on train and validation and 91% on test!
…ed for later use as well as the entry from edge_label_index_dict
added 8 commits
July 25, 2022 18:05
…se having an import conflict with the client package also called `typedb`.
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This was referenced Jul 27, 2022
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added 9 commits
July 27, 2022 14:42
… removed query sampling capabilities which were poorly documented and never used.
…lines (it ignores patterns beginning `--`)
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Approved for the build only. The API contains many changes and most of them are fundamental. They will be reviewed later in a longer discussion (most probably in person) with James and Joshua. |
lolski
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Jul 28, 2022
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What is the difference between requirements.txt and install_requires.txt?
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We discussed this in-person: install_requires.txt is used to fill the field of the same name for PyPi. We need this because the assemble-pip target doesn't support the flags that we need in the requirements.txt file. This is an issue and should be resolved better.
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What is the goal of this PR?
Migrate the ethos of TypeDB-ML to be a library to support machine learning using existing graph learning frameworks, starting with support for PyTorch Geometric and NetworkX to support in-memory graphs and general-purpose graph algorithms.
What are the changes implemented in this PR?
Solves #44