def forward_pass(self, sentences: Union[(List[DataPoint], DataPoint)], return_label_candidates: bool=False):
    'This method does a forward pass through the model given a list of data points as input.\n        Returns the tuple (scores, labels) if return_label_candidates = False, where scores are a tensor of logits\n        produced by the decoder and labels are the string labels for each data point.\n        Returns the tuple (scores, labels, data_points, candidate_labels) if return_label_candidates = True,\n        where data_points are the data points to which labels are added (commonly either Sentence or Token objects)\n        and candidate_labels are empty Label objects for each prediction (depending on the task Label,\n        SpanLabel or RelationLabel).'
    raise NotImplementedError
This method does a forward pass through the model given a list of data points as input.
Returns the tuple (scores, labels) if return_label_candidates = False, where scores are a tensor of logits
produced by the decoder and labels are the string labels for each data point.
Returns the tuple (scores, labels, data_points, candidate_labels) if return_label_candidates = True,
where data_points are the data points to which labels are added (commonly either Sentence or Token objects)
and candidate_labels are empty Label objects for each prediction (depending on the task Label,
SpanLabel or RelationLabel).
def forward_pass(self, sentences: Union[(List[DataPoint], DataPoint)], return_label_candidates: bool=False):
    'This method does a forward pass through the model given a list of data points as input.\n        Returns the tuple (scores, labels) if return_label_candidates = False, where scores are a tensor of logits\n        produced by the decoder and labels are the string labels for each data point.\n        Returns the tuple (scores, labels, data_points, candidate_labels) if return_label_candidates = True,\n        where data_points are the data points to which labels are added (commonly either Sentence or Token objects)\n        and candidate_labels are empty Label objects for each prediction (depending on the task Label,\n        SpanLabel or RelationLabel).'
    raise NotImplementedError