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submission configs OBS and iRand
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‎config/snippets/datasets/GCounteRGANcentr_and_weights.json

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‎config/snippets/datasets/CLEARpadding_centr_and_weights_and_causality.json renamed to ‎config/snippets/datasets/centr_weights_causality_multpadding.json

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{
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"manipulators": [
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{ "class": "src.dataset.manipulators.CLEAR_manipulator.CLEARPadding", "parameters": {} },
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{ "class": "src.dataset.manipulators.multpadding.PaddingGCounteRGAN", "parameters": {} },
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{ "class": "src.dataset.manipulators.causality.Causality", "parameters": {} },
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{ "class": "src.dataset.manipulators.centralities.NodeCentrality", "parameters": {} },
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{ "class": "src.dataset.manipulators.weights.EdgeWeights", "parameters": {} }

‎config/snippets/do-pairs/DBLP_v1_GCN.json

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"oracle": {
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"class": "src.oracle.nn.torch.OracleTorch",
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"parameters": {
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"epochs": 100,
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"epochs": 200,
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"batch_size": 64,
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"optimizer": {
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"class": "torch.optim.AdamW",
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"parameters": {
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"lr":0.005597827355896938,
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"weight_decay":0.022451620056299467
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"lr":0.004,
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"weight_decay":0
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}
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},
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"loss_fn": {
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"model": {
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"class": "src.oracle.nn.gcn.DownstreamGCN",
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"parameters": {
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"num_conv_layers":5,
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"num_dense_layers":9,
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"conv_booster":2,
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"linear_decay":0.3211868888719398
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"num_conv_layers":4,
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"num_dense_layers":2,
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"conv_booster":5,
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"linear_decay":1
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}
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}
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}

‎config/submission/DBLP_v1_GCN_OBS_fold0.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 0, "retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1,"retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights_and_causality.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_OBS_fold1.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 1, "retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1,"retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights_and_causality.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_OBS_fold2.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 2, "retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1,"retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights_and_causality.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_OBS_fold3.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 3, "retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1,"retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights_and_causality.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_OBS_fold4.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 4, "retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1,"retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights_and_causality.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_iRand_fold0.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 0,"retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1, "retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_iRand_fold1.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 1,"retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1, "retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_iRand_fold2.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 2,"retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1, "retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_iRand_fold3.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 3,"retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1, "retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎config/submission/DBLP_v1_GCN_iRand_fold4.jsonc

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{
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"experiment" : {
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"scope": "dblp_v1_configs",
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"scope": "dblp_v1_submission",
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"parameters" : {
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"lock_release_tout":120,
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"propagate":[
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{"in_sections" : ["explainers"],"params" : {"fold_id": 4,"retrain": false}},
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{"in_sections" : ["do-pairs/oracle"],"params" : {"fold_id": -1, "retrain": false}},
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_and_weights.json"}}
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{"in_sections": ["do-pairs/dataset"],"params": {"compose_man" : "config/snippets/datasets/centr_weights_causality_multpadding.json"}}
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]
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}
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},

‎environment.yml

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‎hpsearch/config/DBLP_v1_GCN.json

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{
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"dataset": {
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"class": "src.dataset.dataset_base.Dataset",
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"parameters": {
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"generator": {
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"class": "src.dataset.generators.dblp_v1.DBLP",
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"parameters": {"data_dir": "data/datasets/DBLP_v1/", "dataset_name": "DBLP_v1"}
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}
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}
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},
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"oracle":{
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"class": "src.oracle.nn.torch.OracleTorch",
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"parameters": {
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"epochs": 200,
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"batch_size": 64,
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"optimizer": {
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"class": "torch.optim.AdamW",
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"parameters": {
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"lr":0.004,
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"weight_decay":0
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}
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},
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"loss_fn": {
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"class": "torch.nn.CrossEntropyLoss",
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"parameters": {
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"reduction":"mean"
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}
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},
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"model": {
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"class": "src.oracle.nn.gcn.DownstreamGCN",
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"parameters": {
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"num_conv_layers":4,
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"num_dense_layers":2,
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"conv_booster":5,
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"linear_decay":1
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}
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}
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}
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}
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}

‎src/dataset/generators/dblp_v1.py

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node_features['value'] = self.normalize(node_features['value'])
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assert np.all(node_features['value'].between(0,1)) #values are in [0,1]
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return node_features[['type', 'value']].values
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return node_features[['type', 'value']].to_numpy()

‎src/dataset/manipulators/CLEAR_manipulator.py

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‎src/dataset/manipulators/GCounteRGAN_manipulator.py renamed to ‎src/dataset/manipulators/multpadding.py

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import networkx as nx
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import numpy as np
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from src.dataset.manipulators.base import BaseManipulator
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class PaddingGCounteRGAN(BaseManipulator):
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def node_info(self, instance):
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adj = instance.data
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n_nodes=adj.shape[0]
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n_nodes=instance.num_nodes
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mult=4
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if (n_nodes==0):
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instance.data=np.pad(instance.data,((0,num_padding),(0,num_padding)),'constant',constant_values=0)
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instance.node_features=np.pad(instance.node_features,((0,num_padding),(0,0)),'constant',constant_values=0)
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return {}
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return {}

‎src/dataset/manipulators/padding.py

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import numpy as np
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from src.dataset.manipulators.base import BaseManipulator

‎src/dataset/manipulators/weights.py

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import numpy as np
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from src.dataset.manipulators.base import BaseManipulator

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