class_docstr: FastAP - loss layer definition
  
  This class implements the FastAP loss from the following paper:
  "Deep Metric Learning to Rank",
  F. Cakir, K. He, X. Xia, B. Kulis, S. Sclaroff. CVPR 2019
class_docstr_tok: ["FastAP","-","loss","layer","definition","This","class","implements","the","FastAP","loss","from","the","following","paper",":","''","Deep","Metric","Learning","to","Rank","''",",","F.","Cakir",",","K.","He",",","X.","Xia",",","B.","Kulis",",","S.","Sclaroff",".","CVPR","2019"]
code: def forward(self, batch, labels):
      return OriginalImplementationFastAP.apply(
          batch, labels, self.num_bins
      )
  
file_path: pytorch-metric-learning/tests/losses/test_fastap_loss.py
imports: import torch
  from torch.autograd import Variable
  import unittest
  from pytorch_metric_learning.losses import FastAPLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 2 for calling the OriginalImplementationFastAPLoss obj's underlying member method code with example usage: obj.forward(batch, labels) and returns: OriginalImplementationFastAP