Running a job keeps appending fbk15k-237 to my entity file ids even if I try to manually override it

[JothamWong]

Hi,

Here is my config.yaml file

dataset: name: wn18 num_entities: 40943 num_relations: 18 files: train: filename: train.del type: triples valid: filename: valid.del type: triples entity_ids: filename: entity_ids.del type: map relation_ids: filename: relation_ids.del type: map entity_strings: filename: entity_strings.del type: map relation_strings: filename: relation_ids.del entity_ranking: metrics_per: relation_type: true eval: batch_size: 256 trace_level: example import:

• rescal lookup_embedder: dim: 256 initialize: xavieruniform initializeargs: normal: mean: 0.0 std: 0.0027452953967162064 uniform_: a: -0.7461025531688481 xaviernormal: gain: 1.0 xavieruniform: gain: 1.0 model: rescal negative_sampling: implementation: batch num_samples: p: -1 rescal: entity_embedder: dropout: 0.46531374032890227 regularize_weight: 5.116940665766654e-09 relation_embedder: dropout: 0.38594622673484935 regularize_weight: 2.5263177120255504e-08 train: auto_correct: true batch_size: 256 loss_arg: 1.0 lr_scheduler: ReduceLROnPlateau lr_scheduler_args: factor: 0.95 mode: max patience: 6 threshold: 0.0001 max_epochs: 400 optimizer_args: lr: 0.164019723382278 type: 1vsAll valid: early_stopping: min_threshold: epochs: 50 metric_value: 0.05 patience: 10

Even though I have manually set the dataset to wn18, the entity_ids keep getting fbk15k-237 appended to them which causes an error. I don't understand why this is happening.

Here is the error code

OSError: File d:\jetbrains\pycharmprojects\knowledgeinjection\data\kge\data\wn18\fbk15k-237-entity_ids.del for key entity_ids could not be found

[JothamWong]

Even running the default argument which uses the toy complex search results in the exact same issue.

[AdrianKs]

Hi, could you please post your dataset.yaml which is localted in the datafolder of wn18, additionally. This will help to debug this problem.

[JothamWong]

Hello, here is the dataset.yaml located in my wn18 folder

dataset: files.entity_ids.filename: entity_ids.del files.entity_ids.type: map files.entity_strings.filename: entity_strings.del files.entity_strings.type: idmap files.relation_ids.filename: relation_ids.del files.relation_ids.type: map files.test.filename: test.del files.test.size: 5000 files.test.split_type: test files.test.type: triples files.test_without_unseen.filename: test_without_unseen.del files.test_without_unseen.size: 5000 files.test_without_unseen.split_type: test files.test_without_unseen.type: triples files.train.filename: train.del files.train.size: 141442 files.train.split_type: train files.train.type: triples files.train_sample.filename: train_sample.del files.train_sample.size: 5000 files.train_sample.split_type: train files.train_sample.type: triples files.valid.filename: valid.del files.valid.size: 5000 files.valid.split_type: valid files.valid.type: triples files.valid_without_unseen.filename: valid_without_unseen.del files.valid_without_unseen.size: 5000 files.valid_without_unseen.split_type: valid files.valid_without_unseen.type: triples name: wn18 num_entities: 40943 num_relations: 18