class_docstr: Output layer for pair (two-tower) regression models. Accepts two embedding tensors,
  and computes cosine similarity. The loss is between regression label and cosine
  similarity.
code: def __init__(self, loss_fn: Union[MSELoss, MAELoss]) -> None:
      super().__init__()
      self.loss_fn = loss_fn
      log_class_usage(__class__)
  
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from pytext.config.component import create_loss
  from pytext.loss import MAELoss, MSELoss
  from pytext.utils.usage import log_class_usage
  from .output_layer_base import OutputLayerBase
label_desc: Use image node_id 2 to create a new PairwiseCosineRegressionOutputLayer object from inherited base classes: OutputLayerBase with example: obj = PairwiseCosineRegressionOutputLayer(loss_fn)