DataLoader

class marius.data.DataLoader

__init__(self: marius._data.DataLoader, graph_storage: GraphModelStorage, learning_task: str, training_config: marius._config.TrainingConfig, evaluation_config: marius._config.EvaluationConfig, encoder_config: marius._config.EncoderConfig) → None

__init__(self: marius._data.DataLoader, graph_storage: GraphModelStorage, learning_task: str, batch_size: int = 1000, neg_sampler: marius._data.samplers.NegativeSampler = None, nbr_sampler: marius._data.samplers.NeighborSampler = None, train: bool = False) → None

__init__(self: marius._data.DataLoader, edges: Optional[torch.Tensor], learning_task: str, nodes: Optional[torch.Tensor] = None, node_features: Optional[torch.Tensor] = None, node_embeddings: Optional[torch.Tensor] = None, node_optim_state: Optional[torch.Tensor] = None, node_labels: Optional[torch.Tensor] = None, train_edges: Optional[torch.Tensor] = None, batch_size: int = 1000, neg_sampler: marius._data.samplers.NegativeSampler = None, nbr_sampler: marius._data.samplers.NeighborSampler = None, filter_edges: List[torch.Tensor] = [], train: bool = False) → None

getBatch(self: marius._data.DataLoader, device: Optional[torch.device] = None, perform_map: bool = True) → marius._data.Batch

property all_read

property batch_id_offset

property batches

property batches_left

property batches_processed

clearBatches(self: marius._data.DataLoader) → None

property current_edge

edgeSample(self: marius._data.DataLoader, batch: marius._data.Batch) → None

property edge_buckets_per_buffer

property edge_sampler

epochComplete(self: marius._data.DataLoader) → bool

property epochs_processed

property evaluation_config

property evaluation_negative_sampler

property evaluation_neighbor_sampler

finishedBatch(self: marius._data.DataLoader) → None

getBatchesProcessed(self: marius._data.DataLoader) → int

getEpochsProcessed(self: marius._data.DataLoader) → int

getNextBatch(self: marius._data.DataLoader) → marius._data.Batch

getNumEdges(self: marius._data.DataLoader) → int

property graph_storage

hasNextBatch(self: marius._data.DataLoader) → bool

initializeBatches(self: marius._data.DataLoader, prepare_encode: bool = False) → None

isTrain(self: marius._data.DataLoader) → bool

loadCPUParameters(self: marius._data.DataLoader, batch: marius._data.Batch) → None

loadGPUParameters(self: marius._data.DataLoader, batch: marius._data.Batch) → None

loadStorage(self: marius._data.DataLoader) → None

property negative_sampler

property neighbor_sampler

nextEpoch(self: marius._data.DataLoader) → None

nodeSample(self: marius._data.DataLoader, batch: marius._data.Batch) → None

property node_ids_per_buffer

setActiveEdges(self: marius._data.DataLoader) → None

setActiveNodes(self: marius._data.DataLoader) → None

setBufferOrdering(self: marius._data.DataLoader) → None

setTestSet(self: marius._data.DataLoader) → None

setTrainSet(self: marius._data.DataLoader) → None

setValidationSet(self: marius._data.DataLoader) → None

property train

property training_config

property training_negative_sampler

property training_neighbor_sampler

unloadStorage(self: marius._data.DataLoader, write: bool = False) → None

updateEmbeddings(self: marius._data.DataLoader, batch: marius._data.Batch, gpu: bool = False) → None