class_docstr: Subject verb agreement as verb number predicion (binary classification).
class_docstr_tok: ["Subject","verb","agreement","as","verb","number","predicion","(","binary","classification",")","."]
docstr: Specify the set of evaluation metrics for this problem.
  
  Returns:
    List of evaluation metrics of interest.
docstr_tok: ["Specify","the","set","of","evaluation","metrics","for","this","problem",".","Returns",":","List","of","evaluation","metrics","of","interest","."]
code: def eval_metrics(self):
      """Specify the set of evaluation metrics for this problem.
  
      Returns:
        List of evaluation metrics of interest.
      """
      # TODO(dehghani): Implement accuracy of the target word as a t2t metric.
      return [metrics.Metrics.ACC]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import csv
  import gzip
  import os
  import random
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 9 for calling the SvaNumberPrediction obj's underlying member method code with example usage: obj.eval_metrics() and returns: list