diff --git a/configs/dataset/simplicial/karate_club.yaml b/configs/dataset/simplicial/karate_club.yaml deleted file mode 100755 index 473ba7aa..00000000 --- a/configs/dataset/simplicial/karate_club.yaml +++ /dev/null @@ -1,24 +0,0 @@ -_target_: topobenchmark.data.loaders.SimplicialLoader - -# Data definition -parameters: - data_domain: simplicial - data_type: social - data_name: KarateClub - data_dir: ${paths.data_dir}/${dataset.parameters.data_domain}/${dataset.parameters.data_type}/${dataset.parameters.data_name} - data_split_dir: ${paths.data_dir}/data_splits/${dataset.parameters.data_name} - - # Dataset parameters - num_features: 2 - num_classes: 2 - task: classification - loss_type: cross_entropy - monitor_metric: accuracy - task_level: node - data_seed: 0 - - # Dataloader parameters - batch_size: 128 # Needs to be divisible by the number of devices (e.g., if in a distributed setup) - # train_val_test_split: [55_000, 5_000, 10_000] - num_workers: 0 - pin_memory: False diff --git a/configs/model/cell/can.yaml b/configs/model/cell/can.yaml index eebbffa1..3722a2b5 100755 --- a/configs/model/cell/can.yaml +++ b/configs/model/cell/can.yaml @@ -30,12 +30,12 @@ backbone_wrapper: _partial_: true wrapper_name: CANWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/cell/cccn.yaml b/configs/model/cell/cccn.yaml index 51143266..96ac9058 100755 --- a/configs/model/cell/cccn.yaml +++ b/configs/model/cell/cccn.yaml @@ -24,12 +24,12 @@ backbone_wrapper: _partial_: true wrapper_name: CCCNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/cell/ccxn.yaml b/configs/model/cell/ccxn.yaml index cfd9ad87..40a289cf 100755 --- a/configs/model/cell/ccxn.yaml +++ b/configs/model/cell/ccxn.yaml @@ -26,12 +26,12 @@ backbone_wrapper: _partial_: true wrapper_name: CCXNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/cell/cwn.yaml b/configs/model/cell/cwn.yaml index dd500a85..86062bb0 100755 --- a/configs/model/cell/cwn.yaml +++ b/configs/model/cell/cwn.yaml @@ -23,12 +23,12 @@ backbone_wrapper: _partial_: true wrapper_name: CWNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/cell/topotune.yaml b/configs/model/cell/topotune.yaml index bfa46286..d395390d 100755 --- a/configs/model/cell/topotune.yaml +++ b/configs/model/cell/topotune.yaml @@ -39,12 +39,12 @@ backbone_wrapper: _partial_: true wrapper_name: TuneWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/cell/topotune_onehasse.yaml b/configs/model/cell/topotune_onehasse.yaml index 8d7cae8c..a2d41177 100644 --- a/configs/model/cell/topotune_onehasse.yaml +++ b/configs/model/cell/topotune_onehasse.yaml @@ -38,12 +38,12 @@ backbone_wrapper: _partial_: true wrapper_name: TuneWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/graph/gat.yaml b/configs/model/graph/gat.yaml index 8c71b06d..e2bf7709 100755 --- a/configs/model/graph/gat.yaml +++ b/configs/model/graph/gat.yaml @@ -26,12 +26,12 @@ backbone_wrapper: _partial_: true wrapper_name: GNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: NoReadOut # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/graph/gcn.yaml b/configs/model/graph/gcn.yaml index d54dd9ea..a200c8e6 100755 --- a/configs/model/graph/gcn.yaml +++ b/configs/model/graph/gcn.yaml @@ -23,12 +23,12 @@ backbone_wrapper: _partial_: true wrapper_name: GNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: NoReadOut # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/graph/gcn_dgm.yaml b/configs/model/graph/gcn_dgm.yaml index 5f07465c..e5ed7ac9 100755 --- a/configs/model/graph/gcn_dgm.yaml +++ b/configs/model/graph/gcn_dgm.yaml @@ -26,12 +26,12 @@ backbone_wrapper: _partial_: true wrapper_name: GNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: NoReadOut # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/graph/gin.yaml b/configs/model/graph/gin.yaml index 816affa7..c05336e6 100755 --- a/configs/model/graph/gin.yaml +++ b/configs/model/graph/gin.yaml @@ -23,12 +23,12 @@ backbone_wrapper: _partial_: true wrapper_name: GNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: NoReadOut # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/graph/graph_mlp.yaml b/configs/model/graph/graph_mlp.yaml index 050e82f8..20374c0f 100755 --- a/configs/model/graph/graph_mlp.yaml +++ b/configs/model/graph/graph_mlp.yaml @@ -27,12 +27,12 @@ backbone_wrapper: _partial_: true wrapper_name: GraphMLPWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: NoReadOut # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/hypergraph/alldeepset.yaml b/configs/model/hypergraph/alldeepset.yaml index fe6a5e4b..4c9b6cbc 100755 --- a/configs/model/hypergraph/alldeepset.yaml +++ b/configs/model/hypergraph/alldeepset.yaml @@ -31,12 +31,12 @@ backbone_wrapper: _partial_: true wrapper_name: HypergraphWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/hypergraph/allsettransformer.yaml b/configs/model/hypergraph/allsettransformer.yaml index 6c35a05a..70b1c66f 100755 --- a/configs/model/hypergraph/allsettransformer.yaml +++ b/configs/model/hypergraph/allsettransformer.yaml @@ -25,12 +25,12 @@ backbone_wrapper: _partial_: true wrapper_name: HypergraphWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/hypergraph/edgnn.yaml b/configs/model/hypergraph/edgnn.yaml index 53727d1a..2156beb1 100755 --- a/configs/model/hypergraph/edgnn.yaml +++ b/configs/model/hypergraph/edgnn.yaml @@ -26,12 +26,12 @@ backbone_wrapper: _partial_: true wrapper_name: HypergraphWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/hypergraph/unignn.yaml b/configs/model/hypergraph/unignn.yaml index 54ba46e3..d3126794 100755 --- a/configs/model/hypergraph/unignn.yaml +++ b/configs/model/hypergraph/unignn.yaml @@ -21,12 +21,12 @@ backbone_wrapper: _partial_: true wrapper_name: HypergraphWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/hypergraph/unignn2.yaml b/configs/model/hypergraph/unignn2.yaml index d61dc28f..e99b0c6f 100755 --- a/configs/model/hypergraph/unignn2.yaml +++ b/configs/model/hypergraph/unignn2.yaml @@ -25,12 +25,12 @@ backbone_wrapper: _partial_: true wrapper_name: HypergraphWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/san.yaml b/configs/model/simplicial/san.yaml index 7973ef47..67c45d62 100755 --- a/configs/model/simplicial/san.yaml +++ b/configs/model/simplicial/san.yaml @@ -27,12 +27,12 @@ backbone_wrapper: _partial_: true wrapper_name: SANWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/sccn.yaml b/configs/model/simplicial/sccn.yaml index 0c90eb62..7c34a6f1 100755 --- a/configs/model/simplicial/sccn.yaml +++ b/configs/model/simplicial/sccn.yaml @@ -22,12 +22,12 @@ backbone_wrapper: _partial_: true wrapper_name: SCCNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/sccnn.yaml b/configs/model/simplicial/sccnn.yaml index 6de88175..3b11ea34 100755 --- a/configs/model/simplicial/sccnn.yaml +++ b/configs/model/simplicial/sccnn.yaml @@ -35,12 +35,12 @@ backbone_wrapper: _partial_: true wrapper_name: SCCNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/sccnn_custom.yaml b/configs/model/simplicial/sccnn_custom.yaml index 1b4a23f7..1617670d 100755 --- a/configs/model/simplicial/sccnn_custom.yaml +++ b/configs/model/simplicial/sccnn_custom.yaml @@ -35,12 +35,12 @@ backbone_wrapper: _partial_: true wrapper_name: SCCNNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/scn.yaml b/configs/model/simplicial/scn.yaml index d55aa572..1cfce74e 100755 --- a/configs/model/simplicial/scn.yaml +++ b/configs/model/simplicial/scn.yaml @@ -26,12 +26,12 @@ backbone_wrapper: _partial_: true wrapper_name: SCNWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/topotune.yaml b/configs/model/simplicial/topotune.yaml index 6c0228b3..7ad639d7 100755 --- a/configs/model/simplicial/topotune.yaml +++ b/configs/model/simplicial/topotune.yaml @@ -39,12 +39,12 @@ backbone_wrapper: _partial_: true wrapper_name: TuneWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/model/simplicial/topotune_onehasse.yaml b/configs/model/simplicial/topotune_onehasse.yaml index 01c0bd35..e903adbd 100644 --- a/configs/model/simplicial/topotune_onehasse.yaml +++ b/configs/model/simplicial/topotune_onehasse.yaml @@ -38,12 +38,12 @@ backbone_wrapper: _partial_: true wrapper_name: TuneWrapper out_channels: ${model.feature_encoder.out_channels} - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} readout: _target_: topobenchmark.nn.readouts.${model.readout.readout_name} readout_name: PropagateSignalDown # Use in case readout is not needed Options: PropagateSignalDown - num_cell_dimensions: ${infere_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider + num_cell_dimensions: ${infer_num_cell_dimensions:${oc.select:model.feature_encoder.selected_dimensions,null},${model.feature_encoder.in_channels}} # The highest order of cell dimensions to consider hidden_dim: ${model.feature_encoder.out_channels} out_channels: ${dataset.parameters.num_classes} task_level: ${dataset.parameters.task_level} diff --git a/configs/transforms/knn.yaml b/configs/transforms/knn.yaml index cc044192..bab757b9 100644 --- a/configs/transforms/knn.yaml +++ b/configs/transforms/knn.yaml @@ -1,2 +1,2 @@ defaults: - - /transforms/data_manipulations@knn: infere_knn_connectivity \ No newline at end of file + - /transforms/data_manipulations@knn: infer_knn_connectivity \ No newline at end of file diff --git a/configs/transforms/tree.yaml b/configs/transforms/tree.yaml index c7ecf7cb..0c691d48 100644 --- a/configs/transforms/tree.yaml +++ b/configs/transforms/tree.yaml @@ -1,2 +1,2 @@ defaults: - - /transforms/data_manipulations@tree: infere_tree \ No newline at end of file + - /transforms/data_manipulations@tree: infer_tree \ No newline at end of file diff --git a/docs/api/transforms/data_manipulations/index.rst b/docs/api/transforms/data_manipulations/index.rst index d6331196..794d0658 100644 --- a/docs/api/transforms/data_manipulations/index.rst +++ b/docs/api/transforms/data_manipulations/index.rst @@ -11,10 +11,10 @@ Data Manipulations .. automodule:: topobenchmark.transforms.data_manipulations.identity_transform :members: -.. automodule:: topobenchmark.transforms.data_manipulations.infere_knn_connectivity +.. automodule:: topobenchmark.transforms.data_manipulations.infer_knn_connectivity :members: -.. automodule:: topobenchmark.transforms.data_manipulations.infere_radius_connectivity +.. automodule:: topobenchmark.transforms.data_manipulations.infer_radius_connectivity :members: .. automodule:: topobenchmark.transforms.data_manipulations.keep_only_connected_component diff --git a/test/data/load/test_datasetloaders.py b/test/data/load/test_datasetloaders.py index 82790a94..2a6acc96 100644 --- a/test/data/load/test_datasetloaders.py +++ b/test/data/load/test_datasetloaders.py @@ -36,8 +36,7 @@ def _gather_config_files(self, base_dir: Path) -> List[str]: """ config_files = [] config_base_dir = base_dir / "configs/dataset" - exclude_datasets = {"karate_club.yaml", - # Below the datasets that have some default transforms with we manually overriten with no_transform, + exclude_datasets = {# Below the datasets that have some default transforms manually overriten with no_transform, # due to lack of default transform for domain2domain "REDDIT-BINARY.yaml", "IMDB-MULTI.yaml", "IMDB-BINARY.yaml", #"ZINC.yaml" } diff --git a/test/transforms/data_manipulations/test_ConnectivityTransforms.py b/test/transforms/data_manipulations/test_ConnectivityTransforms.py index 4eb1ba1f..4d95be5b 100644 --- a/test/transforms/data_manipulations/test_ConnectivityTransforms.py +++ b/test/transforms/data_manipulations/test_ConnectivityTransforms.py @@ -28,19 +28,19 @@ def setup_method(self): ) # Initialize transforms - self.infere_by_knn = InfereKNNConnectivity(args={"k": 3}) - self.infere_by_radius = InfereRadiusConnectivity(args={"r": 1.0}) + self.infer_by_knn = InfereKNNConnectivity(args={"k": 3}) + self.infer_by_radius = InfereRadiusConnectivity(args={"r": 1.0}) - def test_infere_knn_connectivity(self): + def test_infer_knn_connectivity(self): """Test inferring connectivity using k-nearest neighbors.""" - data = self.infere_by_knn(self.data.clone()) + data = self.infer_by_knn(self.data.clone()) assert "edge_index" in data, "No edges in Data object" assert data.edge_index.size(0) == 2 assert data.edge_index.size(1) > 0 def test_radius_connectivity(self): """Test inferring connectivity by radius.""" - data = self.infere_by_radius(self.data.clone()) + data = self.infer_by_radius(self.data.clone()) assert "edge_index" in data, "No edges in Data object" assert data.edge_index.size(0) == 2 assert data.edge_index.size(1) > 0 \ No newline at end of file diff --git a/test/utils/test_config_resolvers.py b/test/utils/test_config_resolvers.py index 6da4697f..d7230397 100644 --- a/test/utils/test_config_resolvers.py +++ b/test/utils/test_config_resolvers.py @@ -5,7 +5,7 @@ import hydra from topobenchmark.utils.config_resolvers import ( infer_in_channels, - infere_num_cell_dimensions, + infer_num_cell_dimensions, get_default_metrics, get_default_transform, get_monitor_metric, @@ -109,10 +109,10 @@ def test_infer_in_channels(self): def test_infer_num_cell_dimensions(self): """Test infer_num_cell_dimensions.""" - out = infere_num_cell_dimensions(None, [7, 7, 7]) + out = infer_num_cell_dimensions(None, [7, 7, 7]) assert out == 3 - out = infere_num_cell_dimensions([1, 2, 3], [7, 7]) + out = infer_num_cell_dimensions([1, 2, 3], [7, 7]) assert out == 3 def test_get_default_metrics(self): diff --git a/topobenchmark/run.py b/topobenchmark/run.py index 0fc58c16..6dc72154 100755 --- a/topobenchmark/run.py +++ b/topobenchmark/run.py @@ -30,7 +30,7 @@ get_monitor_mode, get_required_lifting, infer_in_channels, - infere_num_cell_dimensions, + infer_num_cell_dimensions, ) rootutils.setup_root(__file__, indicator=".project-root", pythonpath=True) @@ -71,7 +71,7 @@ "infer_in_channels", infer_in_channels, replace=True ) OmegaConf.register_new_resolver( - "infere_num_cell_dimensions", infere_num_cell_dimensions, replace=True + "infer_num_cell_dimensions", infer_num_cell_dimensions, replace=True ) OmegaConf.register_new_resolver( "parameter_multiplication", lambda x, y: int(int(x) * int(y)), replace=True diff --git a/topobenchmark/transforms/data_manipulations/infere_knn_connectivity.py b/topobenchmark/transforms/data_manipulations/infere_knn_connectivity.py index 4c7ddc66..70fd87e1 100644 --- a/topobenchmark/transforms/data_manipulations/infere_knn_connectivity.py +++ b/topobenchmark/transforms/data_manipulations/infere_knn_connectivity.py @@ -17,7 +17,7 @@ class InfereKNNConnectivity(torch_geometric.transforms.BaseTransform): def __init__(self, **kwargs): super().__init__() - self.type = "infere_knn_connectivity" + self.type = "infer_knn_connectivity" self.parameters = kwargs def __repr__(self) -> str: diff --git a/topobenchmark/transforms/data_manipulations/infere_radius_connectivity.py b/topobenchmark/transforms/data_manipulations/infere_radius_connectivity.py index 5dc2471c..0e5d9bf3 100644 --- a/topobenchmark/transforms/data_manipulations/infere_radius_connectivity.py +++ b/topobenchmark/transforms/data_manipulations/infere_radius_connectivity.py @@ -17,7 +17,7 @@ class InfereRadiusConnectivity(torch_geometric.transforms.BaseTransform): def __init__(self, **kwargs): super().__init__() - self.type = "infere_radius_connectivity" + self.type = "infer_radius_connectivity" self.parameters = kwargs def __repr__(self) -> str: diff --git a/topobenchmark/utils/config_resolvers.py b/topobenchmark/utils/config_resolvers.py index e65e77f0..92be27b2 100644 --- a/topobenchmark/utils/config_resolvers.py +++ b/topobenchmark/utils/config_resolvers.py @@ -234,7 +234,7 @@ def check_for_type_feature_lifting(transforms, lifting): return [dataset.parameters.num_features[0]] -def infere_num_cell_dimensions(selected_dimensions, in_channels): +def infer_num_cell_dimensions(selected_dimensions, in_channels): r"""Infer the length of a list. Parameters