SYMBOL INDEX (423 symbols across 52 files)

FILE: inductive_lp/datasets/ind_dataset.py
  class InductiveDataset (line 3) | class InductiveDataset(DataSet):
    method __init__ (line 5) | def __init__(self,
  class Ind_FB15k237 (line 37) | class Ind_FB15k237(InductiveDataset):
    method __init__ (line 39) | def __init__(self,
  class Ind_WN18RR (line 48) | class Ind_WN18RR(InductiveDataset):
    method __init__ (line 50) | def __init__(self,
  class Ind_NELL (line 58) | class Ind_NELL(InductiveDataset):
    method __init__ (line 60) | def __init__(self,

FILE: inductive_lp/loops/ilp_evaluator.py
  class ILPRankBasedEvaluator (line 9) | class ILPRankBasedEvaluator(RankBasedEvaluator):
    method __init__ (line 11) | def __init__(
    method _update_ranks_ (line 40) | def _update_ranks_(

FILE: inductive_lp/loops/inductive_slcwa.py
  class InductiveSLCWATrainingLoop (line 27) | class InductiveSLCWATrainingLoop(TrainingLoop):
    method __init__ (line 33) | def __init__(
    method triples_factory (line 62) | def triples_factory(self) -> TriplesFactory:  # noqa: D401
    method num_negs_per_pos (line 67) | def num_negs_per_pos(self) -> int:
    method _create_instances (line 74) | def _create_instances(self, use_tqdm: Optional[bool] = None) -> SLCWAI...
    method _get_batch_size (line 78) | def _get_batch_size(batch: MappedTriples) -> int:  # noqa: D102
    method _process_batch (line 81) | def _process_batch(
    method _mr_loss_helper (line 117) | def _mr_loss_helper(
    method _self_adversarial_negative_sampling_loss_helper (line 132) | def _self_adversarial_negative_sampling_loss_helper(
    method _label_loss_helper (line 144) | def _label_loss_helper(
    method _slice_size_search (line 171) | def _slice_size_search(

FILE: inductive_lp/loops/relation_rank_evaluator.py
  class RelationPredictionRankBasedMetricResults (line 15) | class RelationPredictionRankBasedMetricResults(RankBasedMetricResults):
    method get_metric (line 39) | def get_metric(self, name: str) -> float:  # noqa: D102
    method to_flat_dict (line 68) | def to_flat_dict(self):  # noqa: D102
    method to_df (line 77) | def to_df(self):
  class RelationPredictionRankBasedEvaluator (line 90) | class RelationPredictionRankBasedEvaluator(Evaluator):
    method __init__ (line 91) | def __init__(
    method process_tail_scores_ (line 106) | def process_tail_scores_(
    method process_head_scores_ (line 115) | def process_head_scores_(
    method _update_ranks_ (line 124) | def _update_ranks_(self, true_scores, all_scores):
    method evaluate (line 133) | def evaluate(
    method _get_ranks (line 173) | def _get_ranks(self, rank_type):
    method finalize (line 176) | def finalize(self) -> MetricResults:
    method process_relation_scores_ (line 206) | def process_relation_scores_(
  function get_unique_relation_ids_from_triples_tensor (line 216) | def get_unique_relation_ids_from_triples_tensor(mapped_triples: MappedTr...
  function evaluate (line 220) | def evaluate(
  function _evaluate_batch (line 389) | def _evaluate_batch(
  function create_sparse_positive_filter_ (line 500) | def create_sparse_positive_filter_(

FILE: inductive_lp/model/comp_gcn.py
  class StarE_PyG_Encoder (line 13) | class StarE_PyG_Encoder(nn.Module):
    method __init__ (line 14) | def __init__(self,
    method reset_parameters (line 82) | def reset_parameters(self):
    method forward_base (line 103) | def forward_base(self, graph):

FILE: inductive_lp/model/gnn_layer.py
  class StarEConvLayer (line 15) | class StarEConvLayer(MessagePassing):
    method __init__ (line 18) | def __init__(self, in_channels, out_channels, num_rels, act=lambda x: x,
    method reset_parameters (line 76) | def reset_parameters(self):
    method forward (line 93) | def forward(self, x, edge_index, edge_type, rel_embed,
    method rel_transform (line 231) | def rel_transform(self, ent_embed, rel_embed):
    method qual_transform (line 245) | def qual_transform(self, qualifier_ent, qualifier_rel):
    method qualifier_aggregate (line 263) | def qualifier_aggregate(self, qualifier_emb, rel_part_emb, alpha=0.5, ...
    method update_rel_emb_with_qualifier (line 326) | def update_rel_emb_with_qualifier(self, ent_embed, rel_embed,
    method message (line 381) | def message(self, x_j, x_i, edge_type, rel_embed, edge_norm, mode, ent...
    method update (line 437) | def update(self, aggr_out, mode):
    method aggregate (line 444) | def aggregate(self, inputs: Tensor, index: Tensor,
    method compute_norm (line 477) | def compute_norm(edge_index, num_ent):
    method coalesce_quals (line 501) | def coalesce_quals(self, qual_embeddings, qual_index, num_edges, fill=0):
    method __repr__ (line 532) | def __repr__(self):

FILE: inductive_lp/model/lrga_model.py
  function joint_normalize2 (line 7) | def joint_normalize2(U, V_T):
  function weight_init (line 17) | def weight_init(layer):
  class LowRankAttention (line 25) | class LowRankAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, k, d, dropout):
    method forward (line 34) | def forward(self, x):

FILE: inductive_lp/model/nodepiece_rotate.py
  class NodePieceRotate (line 19) | class NodePieceRotate(Model):
    method __init__ (line 21) | def __init__(self,
    method _reset_parameters_ (line 244) | def _reset_parameters_(self):
    method post_parameter_update (line 282) | def post_parameter_update(self):  # noqa: D102
    method pool_anchors (line 295) | def pool_anchors(self, anc_embs: torch.FloatTensor, mask: Optional[tor...
    method encode_by_index (line 311) | def encode_by_index(self, entities: torch.LongTensor) -> torch.FloatTe...
    method get_all_representations (line 343) | def get_all_representations(self):
    method encode_gnn (line 363) | def encode_gnn(self):
    method encode_gnn_entities (line 384) | def encode_gnn_entities(self, heads, rels, tails):
    method pairwise_interaction_function (line 390) | def pairwise_interaction_function(
    method interaction_function (line 413) | def interaction_function(
    method score_hrt (line 439) | def score_hrt(self, hrt_batch: torch.LongTensor) -> torch.FloatTensor:...
    method score_t (line 473) | def score_t(self, hr_batch: torch.LongTensor) -> torch.FloatTensor:  #...
    method score_h (line 497) | def score_h(self, rt_batch: torch.LongTensor) -> torch.FloatTensor:  #...

FILE: inductive_lp/nodepiece_tokenizer.py
  class NodePiece_Tokenizer (line 14) | class NodePiece_Tokenizer:
    method __init__ (line 21) | def __init__(self,
    method tokenize_kg (line 84) | def tokenize_kg(self):
    method create_all_paths (line 146) | def create_all_paths(self, graph: Graph, top_entities: List = None) ->...

FILE: inductive_lp/run_ilp.py
  function main (line 71) | def main(

FILE: inductive_lp/utils/sample_negatives.py
  function sample_negatives (line 8) | def sample_negatives(valid_triples: TriplesFactory, all_pos: TriplesFact...

FILE: inductive_lp/utils/utils_gcn.py
  class MessagePassing (line 14) | class MessagePassing(torch.nn.Module):
    method __init__ (line 31) | def __init__(self, aggr='add'):
    method propagate (line 40) | def propagate(self, aggr, edge_index, **kwargs):
    method message (line 73) | def message(self, x_j):  # pragma: no cover
    method update (line 83) | def update(self, aggr_out):  # pragma: no cover
  function maybe_num_nodes (line 92) | def maybe_num_nodes(index, num_nodes=None):
  function softmax (line 95) | def softmax(src, index, num_nodes=None):
  function get_param (line 119) | def get_param(shape):
  function weight_init (line 124) | def weight_init(layer):
  function com_mult (line 132) | def com_mult(a, b):
  function conj (line 138) | def conj(a):
  function cconv (line 143) | def cconv(a, b):
  function ccorr (line 148) | def ccorr(a, b):
  function rotate (line 152) | def rotate(h, r):
  function scatter_ (line 162) | def scatter_(name, src, index, dim_size=None):

FILE: lp_rp/datasets/codex.py
  function _urlretrieve (line 45) | def _urlretrieve(url: str, path: str, clean_on_failure: bool = True, str...
  class UnpackedRemoteDataset (line 70) | class UnpackedRemoteDataset(PathDataSet):
    method __init__ (line 73) | def __init__(
    method _help_cache (line 127) | def _help_cache(self, cache_root: Union[None, str, pathlib.Path]) -> p...
  class CoDExSmall (line 144) | class CoDExSmall(UnpackedRemoteDataset):
    method __init__ (line 163) | def __init__(self, create_inverse_triples: bool = False, **kwargs):
  class CoDExMedium (line 183) | class CoDExMedium(UnpackedRemoteDataset):
    method __init__ (line 202) | def __init__(self, create_inverse_triples: bool = False, **kwargs):
  class CoDExLarge (line 220) | class CoDExLarge(UnpackedRemoteDataset):
    method __init__ (line 239) | def __init__(self, create_inverse_triples: bool = False, **kwargs):
  function _main (line 256) | def _main():

FILE: lp_rp/loops/filtered_sampling_loop.py
  class FilteredSLCWATrainingLoop (line 4) | class FilteredSLCWATrainingLoop(SLCWATrainingLoop):
    method num_negs_per_pos_rel (line 7) | def num_negs_per_pos_rel(self) -> int:
    method _mr_loss_helper (line 14) | def _mr_loss_helper(self, positive_scores, negative_scores, _label_smo...

FILE: lp_rp/nodepiece_tokenizer.py
  class NodePiece_Tokenizer (line 14) | class NodePiece_Tokenizer:
    method __init__ (line 21) | def __init__(self,
    method tokenize_kg (line 84) | def tokenize_kg(self):
    method create_all_paths (line 146) | def create_all_paths(self, graph: Graph, top_entities: List = None) ->...

FILE: lp_rp/patch/early_stopping.py
  function is_improvement (line 28) | def is_improvement(
  class EarlyStopper (line 58) | class EarlyStopper(Stopper):
    method __post_init__ (line 101) | def __post_init__(self):
    method should_evaluate (line 115) | def should_evaluate(self, epoch: int) -> bool:
    method number_results (line 120) | def number_results(self) -> int:
    method should_stop (line 124) | def should_stop(self, epoch: int) -> bool:
    method get_summary_dict (line 182) | def get_summary_dict(self) -> Mapping[str, Any]:

FILE: lp_rp/patch/evaluator.py
  function optional_context_manager (line 34) | def optional_context_manager(condition, context_manager):
  class MetricResults (line 44) | class MetricResults:
    method get_metric (line 47) | def get_metric(self, name: str) -> float:
    method to_flat_dict (line 51) | def to_flat_dict(self) -> Mapping[str, Any]:
  class Evaluator (line 56) | class Evaluator(ABC):
    method __init__ (line 64) | def __init__(
    method get_normalized_name (line 77) | def get_normalized_name(cls) -> str:
    method process_tail_scores_ (line 82) | def process_tail_scores_(
    method process_head_scores_ (line 100) | def process_head_scores_(
    method finalize (line 118) | def finalize(self) -> MetricResults:
    method evaluate (line 122) | def evaluate(
    method batch_and_slice (line 172) | def batch_and_slice(
    method _param_size_search (line 246) | def _param_size_search(
    method _check_slicing_availability (line 332) | def _check_slicing_availability(model: Model, batch_size: int) -> None:
  function create_sparse_positive_filter_ (line 345) | def create_sparse_positive_filter_(
  function create_dense_positive_mask_ (line 395) | def create_dense_positive_mask_(
  function filter_scores_ (line 413) | def filter_scores_(
  function evaluate (line 444) | def evaluate(
  function _evaluate_batch (line 616) | def _evaluate_batch(

FILE: lp_rp/pykeen105/negative_sampler.py
  function get_true_subject_and_object_per_graph (line 10) | def get_true_subject_and_object_per_graph(triples):
  class FilteredNegativeSampler (line 36) | class FilteredNegativeSampler(NegativeSampler):
    method __init__ (line 37) | def __init__(self, triples_factory, num_negs_per_pos=None, dataset_nam...
    method sample_entities (line 60) | def sample_entities(self, h, r, t, corrput_head=True):
    method sample (line 78) | def sample(self, positive_batch: torch.LongTensor) -> torch.LongTensor:
  class RelationalNegativeSampler (line 99) | class RelationalNegativeSampler(FilteredNegativeSampler):
    method __init__ (line 101) | def __init__(self, triples_factory, num_negs_per_pos=None, num_negs_pe...
    method num_relations (line 106) | def num_relations(self) -> int:  # noqa: D401
    method sample_relations (line 110) | def sample_relations(self, h, t):
    method sample (line 129) | def sample(self, positive_batch):

FILE: lp_rp/pykeen105/nodepiece_rotate.py
  class NodePieceRotate (line 17) | class NodePieceRotate(Model):
    method __init__ (line 19) | def __init__(self,
    method _reset_parameters_ (line 181) | def _reset_parameters_(self):
    method post_parameter_update (line 216) | def post_parameter_update(self):  # noqa: D102
    method pool_anchors (line 229) | def pool_anchors(self, anc_embs: torch.FloatTensor, mask: Optional[tor...
    method encode_by_index (line 245) | def encode_by_index(self, entities: torch.LongTensor) -> torch.FloatTe...
    method get_all_representations (line 273) | def get_all_representations(self):
    method pairwise_interaction_function (line 289) | def pairwise_interaction_function(
    method interaction_function (line 312) | def interaction_function(
    method score_hrt (line 338) | def score_hrt(self, hrt_batch: torch.LongTensor) -> torch.FloatTensor:...
    method score_t (line 364) | def score_t(self, hr_batch: torch.LongTensor) -> torch.FloatTensor:  #...
    method score_h (line 384) | def score_h(self, rt_batch: torch.LongTensor) -> torch.FloatTensor:  #...

FILE: lp_rp/pykeen105/relation_rank_evaluator.py
  class RelationPredictionRankBasedMetricResults (line 15) | class RelationPredictionRankBasedMetricResults(RankBasedMetricResults):
    method get_metric (line 39) | def get_metric(self, name: str) -> float:  # noqa: D102
    method to_flat_dict (line 68) | def to_flat_dict(self):  # noqa: D102
    method to_df (line 77) | def to_df(self):
  class RelationPredictionRankBasedEvaluator (line 90) | class RelationPredictionRankBasedEvaluator(Evaluator):
    method __init__ (line 91) | def __init__(
    method process_tail_scores_ (line 106) | def process_tail_scores_(
    method process_head_scores_ (line 115) | def process_head_scores_(
    method _update_ranks_ (line 124) | def _update_ranks_(self, true_scores, all_scores):
    method evaluate (line 133) | def evaluate(
    method _get_ranks (line 173) | def _get_ranks(self, rank_type):
    method finalize (line 176) | def finalize(self) -> MetricResults:
    method process_relation_scores_ (line 206) | def process_relation_scores_(
  function get_unique_relation_ids_from_triples_tensor (line 216) | def get_unique_relation_ids_from_triples_tensor(mapped_triples: MappedTr...
  function evaluate (line 220) | def evaluate(
  function _evaluate_batch (line 389) | def _evaluate_batch(
  function create_sparse_positive_filter_ (line 500) | def create_sparse_positive_filter_(

FILE: lp_rp/run_lp.py
  function main (line 70) | def main(

FILE: nc/data_loaders/clean_datasets.py
  function to_sparse_graph (line 14) | def to_sparse_graph(edges, subtype, entoid, prtoid, maxlen):
  function load_clean_pyg (line 42) | def load_clean_pyg(name, subtype, task, inductive="transductive", ind_v=...

FILE: nc/loops/evaluation.py
  function compute_roc_auc (line 9) | def compute_roc_auc(y_true, y_pred):
  function compute_prcauc (line 27) | def compute_prcauc(y_true, y_pred):
  function compute_average_precision (line 41) | def compute_average_precision(y_true, y_pred):
  function hard_accuracy (line 54) | def hard_accuracy(y_true, y_pred):
  function eval_classification (line 60) | def eval_classification(y_true, y_pred):

FILE: nc/loops/loops.py
  function training_loop_pyg_nc (line 12) | def training_loop_pyg_nc(epochs: int,

FILE: nc/loops/sampler.py
  class NodeClSampler (line 6) | class NodeClSampler:
    method __init__ (line 12) | def __init__(self, data: Union[np.array, dict], num_labels: int,
    method generate_labels (line 30) | def generate_labels(self):
    method compute_weights (line 60) | def compute_weights(self, data):
    method get_data (line 69) | def get_data(self):

FILE: nc/models/gnn_encoder.py
  class StarE_PyG_Encoder (line 16) | class StarE_PyG_Encoder(nn.Module):
    method __init__ (line 17) | def __init__(self, config: dict, tokenizer: NodePiece_Tokenizer = None...
    method reset_parameters (line 89) | def reset_parameters(self):
    method post_parameter_update (line 121) | def post_parameter_update(self):
    method forward_base (line 127) | def forward_base(self, graph, drop1, drop2):

FILE: nc/models/gnn_layer.py
  class StarEConvLayer (line 11) | class StarEConvLayer(MessagePassing):
    method __init__ (line 14) | def __init__(self, in_channels, out_channels, num_rels, act=lambda x: x,
    method reset_parameters (line 67) | def reset_parameters(self):
    method forward (line 82) | def forward(self, x, edge_index, edge_type, rel_embed,
    method rel_transform (line 217) | def rel_transform(self, ent_embed, rel_embed):
    method qual_transform (line 231) | def qual_transform(self, qualifier_ent, qualifier_rel):
    method qualifier_aggregate (line 249) | def qualifier_aggregate(self, qualifier_emb, rel_part_emb, alpha=0.5, ...
    method update_rel_emb_with_qualifier (line 312) | def update_rel_emb_with_qualifier(self, ent_embed, rel_embed,
    method message (line 367) | def message(self, x_j, x_i, edge_type, rel_embed, edge_norm, mode, ent...
    method update (line 423) | def update(self, aggr_out, mode):
    method compute_norm (line 430) | def compute_norm(edge_index, num_ent):
    method coalesce_quals (line 457) | def coalesce_quals(self, qual_embeddings, qual_index, num_edges, fill=0):
    method __repr__ (line 488) | def __repr__(self):

FILE: nc/models/lrga_model.py
  function joint_normalize2 (line 7) | def joint_normalize2(U, V_T):
  function weight_init (line 17) | def weight_init(layer):
  class LowRankAttention (line 25) | class LowRankAttention(nn.Module):
    method __init__ (line 26) | def __init__(self, k, d, dropout):
    method forward (line 34) | def forward(self, x):

FILE: nc/models/nc_baselines.py
  class MLP (line 7) | class MLP(nn.Module):
    method __init__ (line 11) | def __init__(self, initial_features, config):
    method forward (line 35) | def forward(self, train_mask):
  class MLP_PyG (line 49) | class MLP_PyG(nn.Module):
    method __init__ (line 53) | def __init__(self, config, tokenizer, graph):
    method reset_parameters (line 82) | def reset_parameters(self):
    method forward (line 92) | def forward(self, graph, train_mask):

FILE: nc/models_nc.py
  class StarE_PyG_NC (line 12) | class StarE_PyG_NC(StarE_PyG_Encoder):
    method __init__ (line 16) | def __init__(self, config: dict, tokenizer: NodePiece_Tokenizer = None...
    method reset_parameters (line 31) | def reset_parameters(self):
    method forward (line 35) | def forward(self, graph, train_mask):

FILE: nc/utils/nodepiece_encoder.py
  class NodePieceEncoder (line 16) | class NodePieceEncoder(nn.Module):
    method __init__ (line 17) | def __init__(self, config: dict, tokenizer: NodePiece_Tokenizer, rel_e...
    method reset_parameters (line 191) | def reset_parameters(self):
    method pool_anchors (line 241) | def pool_anchors(self, anc_embs: torch.FloatTensor, mask: Optional[tor...
    method encode_rels (line 269) | def encode_rels(self, rel_hashes: torch.LongTensor, weights: Optional[...
    method encode_by_index (line 326) | def encode_by_index(self, entities: torch.LongTensor) -> torch.FloatTe...
    method get_all_representations (line 381) | def get_all_representations(self):

FILE: nc/utils/nodepiece_tokenizer.py
  class NodePiece_Tokenizer (line 13) | class NodePiece_Tokenizer:
    method __init__ (line 20) | def __init__(self,
    method tokenize_kg (line 81) | def tokenize_kg(self):
    method create_all_paths (line 137) | def create_all_paths(self, graph: Graph, top_entities: List = None) ->...

FILE: nc/utils/utils.py
  function masked_softmax (line 10) | def masked_softmax(x, m=None, dim=-1):
  function combine (line 28) | def combine(*args: Union[np.ndarray, list, tuple]):
  function print_results (line 66) | def print_results(traces: List):

FILE: nc/utils/utils_gcn.py
  class MessagePassing (line 17) | class MessagePassing(torch.nn.Module):
    method __init__ (line 34) | def __init__(self, aggr='add'):
    method propagate (line 43) | def propagate(self, aggr, edge_index, **kwargs):
    method message (line 76) | def message(self, x_j):  # pragma: no cover
    method update (line 86) | def update(self, aggr_out):  # pragma: no cover
  function maybe_num_nodes (line 95) | def maybe_num_nodes(index, num_nodes=None):
  function softmax (line 98) | def softmax(src, index, num_nodes=None):
  function get_param (line 122) | def get_param(shape):
  function weight_init (line 127) | def weight_init(layer):
  function com_mult (line 135) | def com_mult(a, b):
  function conj (line 141) | def conj(a):
  function cconv (line 146) | def cconv(a, b):
  function ccorr (line 151) | def ccorr(a, b):
  function rotate (line 155) | def rotate(h, r):
  function scatter_ (line 165) | def scatter_(name, src, index, dim_size=None):

FILE: nc/utils/utils_mytorch.py
  class ImproperCMDArguments (line 13) | class ImproperCMDArguments(Exception): pass
  class MismatchedDataError (line 14) | class MismatchedDataError(Exception): pass
  class BadParameters (line 15) | class BadParameters(Exception):
    method __init___ (line 16) | def __init___(self, dErrorArguments):
  class FancyDict (line 22) | class FancyDict(dict):
    method __init__ (line 23) | def __init__(self, *args, **kwargs):
  class Timer (line 27) | class Timer:
    method __enter__ (line 29) | def __enter__(self):
    method __exit__ (line 33) | def __exit__(self, *args):
  function default_eval (line 37) | def default_eval(y_pred, y_true):
  function compute_mask (line 46) | def compute_mask(t: Union[torch.Tensor, np.array], padding_idx=0):
  function convert_nicely (line 60) | def convert_nicely(arg, possible_types=(bool, float, int, str)):
  function parse_args (line 80) | def parse_args(raw_args: List[str], compulsory: List[str] = (), compulso...
  function mt_save_dir (line 141) | def mt_save_dir(parentdir: Path, _newdir: bool = False):
  function mt_save (line 189) | def mt_save(savedir: Path, message: str = None, message_fname: str = Non...
  class SimplestSampler (line 252) | class SimplestSampler:
    method __init__ (line 259) | def __init__(self, data, bs: int = 64):
    method __len__ (line 272) | def __len__(self):
    method __iter__ (line 275) | def __iter__(self):
    method __next__ (line 279) | def __next__(self):

FILE: ogb/ogb_tokenizer.py
  class NodePiece_OGB (line 19) | class NodePiece_OGB:
    method __init__ (line 25) | def __init__(self,
    method tokenize_kg (line 97) | def tokenize_kg(self):
    method create_all_paths (line 166) | def create_all_paths(self, graph: Graph, top_entities: List = None) ->...
    method mine_partitions (line 213) | def mine_partitions(self, anchors) -> Dict[int, List]:
    method bfs_cluster (line 257) | def bfs_cluster(self, cluster: Data, anchors: List, tqdm_pos=None) -> ...
    method mine_parallel (line 314) | def mine_parallel(self, anchors):
    method mining_subp (line 361) | def mining_subp(self, data_point):

FILE: ogb/ogb_wikikg2/dataloader.py
  class TrainDataset (line 11) | class TrainDataset(Dataset):
    method __init__ (line 12) | def __init__(self, triples, nentity, nrelation, negative_sample_size, ...
    method __len__ (line 23) | def __len__(self):
    method __getitem__ (line 26) | def __getitem__(self, idx):
    method collate_fn (line 68) | def collate_fn(data):
  class TestDataset (line 76) | class TestDataset(Dataset):
    method __init__ (line 77) | def __init__(self, triples, args, mode, random_sampling):
    method __len__ (line 87) | def __len__(self):
    method __getitem__ (line 90) | def __getitem__(self, idx):
    method collate_fn (line 110) | def collate_fn(data):
  class BidirectionalOneShotIterator (line 118) | class BidirectionalOneShotIterator(object):
    method __init__ (line 119) | def __init__(self, dataloader_head, dataloader_tail):
    method __next__ (line 124) | def __next__(self):
    method one_shot_iterator (line 133) | def one_shot_iterator(dataloader):

FILE: ogb/ogb_wikikg2/dummy_factory.py
  class DummyTripleFactory (line 1) | class DummyTripleFactory:
    method __init__ (line 7) | def __init__(self, triples, ne, nr):

FILE: ogb/ogb_wikikg2/model.py
  class KGEModel (line 25) | class KGEModel(nn.Module):
    method __init__ (line 26) | def __init__(self, model_name, nentity, nrelation, hidden_dim, gamma, ...
    method pool_anchors (line 159) | def pool_anchors(self, anc_embs: torch.FloatTensor, mask: Optional[tor...
    method encode_by_index (line 178) | def encode_by_index(self, entities: torch.LongTensor) -> torch.FloatTe...
    method forward (line 200) | def forward(self, sample, mode='single'):
    method AutoSF (line 274) | def AutoSF(self, head, relation, tail, mode):
    method PairRE (line 298) | def PairRE(self, head, relation, tail, mode):
    method TransE (line 308) | def TransE(self, head, relation, tail, mode):
    method DistMult (line 317) | def DistMult(self, head, relation, tail, mode):
    method ComplEx (line 326) | def ComplEx(self, head, relation, tail, mode):
    method RotatE (line 343) | def RotatE(self, head, relation, tail, mode):
    method train_step (line 374) | def train_step(model, optimizer, train_iterator, args):
    method test_step (line 433) | def test_step(model, test_triples, args, random_sampling=False):

FILE: ogb/run_ogb.py
  function parse_args (line 31) | def parse_args(args=None):
  function override_config (line 110) | def override_config(args):
  function save_model (line 126) | def save_model(model, optimizer, save_variable_list, args):
  function set_logger (line 156) | def set_logger(args):
  function log_metrics (line 182) | def log_metrics(mode, step, metrics, writer):
  function main (line 191) | def main(args):

FILE: oos_lp/src/common/dataset.py
  class Dataset (line 20) | class Dataset:
    method __init__ (line 21) | def __init__(self, dataset_name, cons_masking=False, mask_prob=0.5, to...
    method read_text (line 40) | def read_text(self, file_path):
    method dataset_stat (line 49) | def dataset_stat(self, triples):
    method read_json (line 71) | def read_json(self, file_path):
    method triple2ids (line 86) | def triple2ids(self, triple):
    method get_ent_id (line 93) | def get_ent_id(self, ent, add_ent=True):
    method get_rel_id (line 101) | def get_rel_id(self, rel):
    method num_ent (line 106) | def num_ent(self):
    method num_rel (line 109) | def num_rel(self):
    method rand_ent_except (line 112) | def rand_ent_except(self, ent):
    method next_pos_batch (line 118) | def next_pos_batch(self, batch_size):
    method generate_neg (line 129) | def generate_neg(self, pos_batch, neg_ratio):
    method next_batch (line 139) | def next_batch(self, batch_size, neg_ratio, device):
    method was_last_batch (line 162) | def was_last_batch(self):
    method num_batch (line 165) | def num_batch(self, batch_size):
    method num_batch_simulated (line 168) | def num_batch_simulated(self, simulate_batch_size):
    method generate_neg_obs (line 171) | def generate_neg_obs(self, obs_triples, new_ent, neg_ratio):

FILE: oos_lp/src/common/measure.py
  class Measure (line 9) | class Measure:
    method __init__ (line 10) | def __init__(self):
    method update (line 18) | def update(self, rank):
    method normalize (line 29) | def normalize(self):
    method print_ (line 39) | def print_(self):

FILE: oos_lp/src/main.py
  function str2bool (line 28) | def str2bool(v):
  function get_parameters (line 38) | def get_parameters():

FILE: oos_lp/src/model/BaseOutKG.py
  class BaseOutKG (line 11) | class BaseOutKG(nn.Module):
    method __init__ (line 12) | def __init__(self, dataset, args, device):
    method build_model (line 21) | def build_model(self):
    method forward (line 24) | def forward(self, triples, mask):
    method cal_score (line 46) | def cal_score(self, obs_ents, new_ents, rels):
    method get_ent_embs (line 51) | def get_ent_embs(self, ent_id):
    method get_new_ent_embs (line 54) | def get_new_ent_embs(self, triples, mask):
    method get_rel_embs (line 57) | def get_rel_embs(self, rel_id):
    method l2_loss (line 60) | def l2_loss(self):
    method find_embedding (line 63) | def find_embedding(self, new_ent, obs_triples):

FILE: oos_lp/src/model/DisMultOutKG.py
  class DisMultOutKG (line 14) | class DisMultOutKG(BaseOutKG):
    method build_model (line 15) | def build_model(self):
    method get_ent_embs (line 28) | def get_ent_embs(self, ent_id):
    method get_rel_embs (line 32) | def get_rel_embs(self, rel_id):
    method get_new_ent_embs (line 35) | def get_new_ent_embs(self, triples, mask):
    method l2_loss (line 56) | def l2_loss(self):
    method get_ent_exc_ids (line 62) | def get_ent_exc_ids(self, obs_triples, new_ent):
    method find_embedding (line 77) | def find_embedding(self, new_ent, obs_triples):
    method infer_emb (line 88) | def infer_emb(self, ent_emb, rel_emb, mask=None):
    method find_neighbors_avg (line 130) | def find_neighbors_avg(self, ent_emb, rel_emb=None, mask=None):

FILE: oos_lp/src/model/dm_tokenized.py
  class TokenizedDistMult (line 10) | class TokenizedDistMult(nn.Module):
    method __init__ (line 12) | def __init__(self,
    method forward (line 29) | def forward(self, triples, mask):
    method get_rel_embs (line 42) | def get_rel_embs(self, rels: torch.LongTensor):
    method get_ent_embs (line 45) | def get_ent_embs(self, entities: torch.LongTensor):
    method reset (line 50) | def reset(self):
    method cal_score (line 53) | def cal_score(self, obs_ents, new_ents, rels):
    method get_ent_exc_ids (line 58) | def get_ent_exc_ids(self, obs_triples, new_ent):
    method prune_tokens (line 73) | def prune_tokens(self, temp_hashes: torch.LongTensor, temp_dist: torch...
    method find_embedding (line 91) | def find_embedding(self, ent_id: int, observed_triples: np.ndarray):

FILE: oos_lp/src/preprocess/dataset_prep.py
  class DatasetPreprocess (line 19) | class DatasetPreprocess:
    method __init__ (line 20) | def __init__(self, dataset_name, smpl_ratio=0.2, spl_ratio=0.5):
    method read_all (line 31) | def read_all(self):
    method make_dataset (line 44) | def make_dataset(self):
    method single_triple_ent (line 54) | def single_triple_ent(self):
    method split_entities (line 67) | def split_entities(self):
    method save_dataset (line 73) | def save_dataset(self):
    method constraint_check (line 91) | def constraint_check(self):
    method separate_triples (line 122) | def separate_triples(self):
    method find_dangling_ent (line 130) | def find_dangling_ent(self):
    method find_dangling_rel (line 134) | def find_dangling_rel(self):
    method explore_split_dataset (line 139) | def explore_split_dataset(self):
    method get_ent_triples (line 183) | def get_ent_triples(self, e_ids, triples, return_ids=False):
    method smpl_new_ent (line 191) | def smpl_new_ent(self):
    method num_ent (line 200) | def num_ent(self):
    method num_rel (line 203) | def num_rel(self):
    method triple2ids (line 206) | def triple2ids(self, triple):
    method ids2triple (line 213) | def ids2triple(self, ids):
    method get_ent_id (line 218) | def get_ent_id(self, ent):
    method get_rel_id (line 223) | def get_rel_id(self, rel):
    method get_ent_str (line 228) | def get_ent_str(self, e_id):
    method get_rel_str (line 233) | def get_rel_str(self, r_id):

FILE: oos_lp/src/tester.py
  class OutKGTester (line 14) | class OutKGTester:
    method __init__ (line 15) | def __init__(self, dataset):
    method test (line 22) | def test(self, model_path, valid_or_test):
    method predict (line 46) | def predict(self, target_triple, new_ent, obs_triples):
    method filter_entities (line 62) | def filter_entities(self, obs_triples, rel_id, head_or_tail):
    method create_queries (line 69) | def create_queries(self, target_triple, head_or_tail, obs_triples):
    method get_rank (line 83) | def get_rank(self, sim_scores):
    method get_unseen_entities (line 90) | def get_unseen_entities(self):
    method get_ent_triples (line 95) | def get_ent_triples(self, ent, valid_or_test):

FILE: oos_lp/src/trainer.py
  class OutKGTrainer (line 20) | class OutKGTrainer:
    method __init__ (line 21) | def __init__(self, dataset, args, tokenizer):
    method l2_loss (line 43) | def l2_loss(self):
    method train (line 46) | def train(self, save=True):

FILE: oos_lp/src/utils.py
  function save_model (line 13) | def save_model(
  function random_new_ent_mask (line 43) | def random_new_ent_mask(triples, mask_prob):

FILE: oos_lp/src/vocab/nodepiece_encoder.py
  class NodePieceEncoder (line 17) | class NodePieceEncoder(nn.Module):
    method __init__ (line 21) | def __init__(self, config: Namespace, tokenizer: NodePiece_Tokenizer, ...
    method reset_parameters (line 139) | def reset_parameters(self):
    method pool_anchors (line 165) | def pool_anchors(self, anc_embs: torch.FloatTensor, mask: Optional[tor...
    method encode_by_index (line 180) | def encode_by_index(self, entities: torch.LongTensor) -> torch.FloatTe...
    method get_all_representations (line 204) | def get_all_representations(self):
    method encode_by_hash (line 217) | def encode_by_hash(self, hashes: torch.LongTensor, distances: torch.Lo...

FILE: oos_lp/src/vocab/nodepiece_tokenizer.py
  class NodePiece_Tokenizer (line 212) | class NodePiece_Tokenizer:
    method __init__ (line 219) | def __init__(self,
    method tokenize_kg (line 282) | def tokenize_kg(self):
    method create_all_paths (line 338) | def create_all_paths(self, graph: Graph, top_entities: List = None) ->...