class_docstr: Pipeline that learns span boundaries.
  
  DOCS: https://spacy.io/api/spanfinder
class_docstr_tok: ["Pipeline","that","learns","span","boundaries",".","DOCS",":","https",":","\/\/spacy.io\/api\/spanfinder"]
docstr: Learn from a batch of documents and gold-standard information,
  updating the pipe's model. Delegates to predict and get_loss.
  examples (Iterable[Example]): A batch of Example objects.
  drop (float): The dropout rate.
  sgd (Optional[thinc.api.Optimizer]): The optimizer.
  losses (Optional[Dict[str, float]]): Optional record of the loss during
      training. Updated using the component name as the key.
  RETURNS (Dict[str, float]): The updated losses dictionary.
  
  DOCS: https://spacy.io/api/spanfinder#update
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code: def update(
      self,
      examples: Iterable[Example],
      *,
      drop: float = 0.0,
      sgd: Optional[Optimizer] = None,
      losses: Optional[Dict[str, float]] = None,
  ) -> Dict[str, float]:
      """Learn from a batch of documents and gold-standard information,
      updating the pipe's model. Delegates to predict and get_loss.
      examples (Iterable[Example]): A batch of Example objects.
      drop (float): The dropout rate.
      sgd (Optional[thinc.api.Optimizer]): The optimizer.
      losses (Optional[Dict[str, float]]): Optional record of the loss during
          training. Updated using the component name as the key.
      RETURNS (Dict[str, float]): The updated losses dictionary.
  
      DOCS: https://spacy.io/api/spanfinder#update
      """
      if losses is None:
          losses = {}
      losses.setdefault(self.name, 0.0)
      predicted = [eg.predicted for eg in examples]
      set_dropout_rate(self.model, drop)
      scores, backprop_scores = self.model.begin_update(predicted)
      loss, d_scores = self.get_loss(examples, scores)
      backprop_scores(d_scores)
      if sgd is not None:
          self.finish_update(sgd)
      losses[self.name] += loss
      return losses
  
imports: from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
  from thinc.api import Config, Model, Optimizer, set_dropout_rate
  from thinc.types import Floats2d
  from ..errors import Errors
  from ..language import Language
  from ..scorer import Scorer
  from ..tokens import Doc, Span
  from ..training import Example
  from ..util import registry
  from .spancat import DEFAULT_SPANS_KEY
  from .trainable_pipe import TrainablePipe
label_desc: Use image node_id 4 for calling the SpanFinder obj's underlying member method code with example usage: obj.update(examples) and returns: losses