GNNExplainer migration
#5967
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GNNExplainer migration
#5967
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Codecov Report
@@ Coverage Diff @@
## master #5967 +/- ##
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- Coverage 86.44% 84.26% -2.18%
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Files 361 362 +1
Lines 20298 20404 +106
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- Hits 17547 17194 -353
- Misses 2751 3210 +459
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Not so sure how to deal with multi-outputs for classification (node/graph). Does it even make sens ? |
wsad1
reviewed
Nov 14, 2022
Co-authored-by: Jinu Sunil <jinu.sunil@gmail.com>
for more information, see https://pre-commit.ci
wsad1
reviewed
Nov 15, 2022
- add test for `shared_mask=False` - rename function only used internally
rusty1s
reviewed
Nov 15, 2022
- add new MaskType - add better information for user in `supports` - typos - change `index` to `node_index`
3 tasks
avgupta456
reviewed
Nov 22, 2022
avgupta456
approved these changes
Nov 22, 2022
wsad1
approved these changes
Nov 23, 2022
rusty1s
approved these changes
Nov 25, 2022
JakubPietrakIntel
pushed a commit
to JakubPietrakIntel/pytorch_geometric
that referenced
this pull request
Nov 25, 2022
- Implements the `GNNExplainer` in the new `explain` module. - Add the argument `node_index` and `target_index` to the `explain.Explainer` class to allow for explanations of model with multi-outputs and specify the node. - Update the examples of the `GNNExplainer` (pyg-team#5924) Co-authored-by: Jinu Sunil <jinu.sunil@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de> Co-authored-by: Abhijit Gupta <avgupta456@gmail.com>
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Hi, |
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rusty1s
added a commit
that referenced
this pull request
Nov 29, 2022
This PR extends the recent `GNNExplainer` work (#5967) to edge classification and edge regression (including link prediction). Draft until the main `GNNExplainer` PR is merged. Progress towards #5925. **Done** - Adds tests for the `subgraph` function in `base.py`. Uses `subgraph([node_idx_1, node_idx_2])` to get the edge k-hop subgraph. - Implements the edge classification and edge regression tasks. Currently only supports a single index into the edge_index. - Adds tests for the edge predictions, similar to the node/graph task tests. **Todo** - Support multiple indexes into the edge_index and/or passing a separate edge_label_index to explain edges not in the graph (ex. negative link prediction). - Create examples to demonstrate edge level explanations. Are there specific datasets/tasks that would be interesting to look at. I would like some preliminary feedback before attempting the above two tasks. I'm also unsure if these additions should be in this PR or a separate one. Co-authored-by: Charles Dufour <dufourc115@gmail.com> Co-authored-by: Charles Dufour <34485907+dufourc1@users.noreply.github.com> Co-authored-by: Jinu Sunil <jinu.sunil@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de>
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GNNExplainerin the newexplainmodule.node_indexandtarget_indexto theexplain.Explainerclass to allow for explanations of model with multi-outputs and specify the node.GNNExplainer(Example of Using the New Explainability Framework #5924)