class_docstr: A base module for training models with PyTorch Lightning.
  
  .. seealso::
      :class:`pykeen.training.training_loop.TrainingLoop`
class_docstr_tok: ["A","base","module","for","training","models","with","PyTorch","Lightning",".","..","seealso",":",":",":","class",":","`","pykeen.training.training_loop.TrainingLoop","`"]
docstr: Perform the prediction or inference step by wrapping :meth:`pykeen.models.ERModel.predict_t`.
  
  :param hr_batch: shape: (batch_size, 2), dtype: long
      The indices of (head, relation) pairs.
  :return: shape: (batch_size, num_entities), dtype: float
      For each h-r pair, the scores for all possible tails.
  
  .. note::
      in lightning, forward defines the prediction/inference actions
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code: def forward(self, hr_batch: torch.LongTensor) -> torch.FloatTensor:
      """
      Perform the prediction or inference step by wrapping :meth:`pykeen.models.ERModel.predict_t`.
  
      :param hr_batch: shape: (batch_size, 2), dtype: long
          The indices of (head, relation) pairs.
      :return: shape: (batch_size, num_entities), dtype: float
          For each h-r pair, the scores for all possible tails.
  
      .. note::
          in lightning, forward defines the prediction/inference actions
      """
      return self.model.predict_t(hr_batch)
  
imports: from abc import abstractmethod
  from typing import Optional
  import click
  import pytorch_lightning
  import torch
  import torch.utils.data
  from class_resolver import ClassResolver, HintOrType, OptionalKwargs
  from pykeen.datasets import dataset_resolver, get_dataset
  from pykeen.datasets.base import Dataset
  from pykeen.losses import Loss, loss_resolver
  from pykeen.models import Model, model_resolver
  from pykeen.models.cli import options
  from pykeen.optimizers import optimizer_resolver
  from pykeen.sampling import NegativeSampler
  from pykeen.training import LCWATrainingLoop, SLCWATrainingLoop
  from pykeen.triples.triples_factory import CoreTriplesFactory
  from pykeen.typing import InductiveMode, OneOrSequence
label_desc: Use image node_id 2 for calling the LitModule obj's underlying member method code with example usage: obj.forward(hr_batch) and returns: self