code: def test_names(self):
      fbeta = FBeta(
          average="macro", make_deterministic=self.make_deterministic
      )
      self.assertEqual(
          ["fscore_macro", "precision_macro", "recall_macro"],
          fbeta.__name__,
      )
      fbeta = FBeta(
          average="micro", make_deterministic=self.make_deterministic
      )
      self.assertEqual(
          ["fscore_micro", "precision_micro", "recall_micro"],
          fbeta.__name__,
      )
      fbeta = FBeta(
          average="micro",
          names=["f", "p", "r"],
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual(["f", "p", "r"], fbeta.__name__)
      fbeta = FBeta(
          average=0, make_deterministic=self.make_deterministic
      )
      self.assertEqual(
          ["fscore_0", "precision_0", "recall_0"], fbeta.__name__
      )
      fbeta = FBeta(
          metric="fscore",
          average="macro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("fscore_macro", fbeta.__name__)
      fbeta = FBeta(
          metric="fscore",
          average="micro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("fscore_micro", fbeta.__name__)
      fbeta = FBeta(
          metric="fscore",
          average=0,
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("fscore_0", fbeta.__name__)
      fbeta = FBeta(
          metric="precision",
          average="macro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("precision_macro", fbeta.__name__)
      fbeta = FBeta(
          metric="precision",
          average="micro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("precision_micro", fbeta.__name__)
      fbeta = FBeta(
          metric="precision",
          average=0,
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("precision_0", fbeta.__name__)
      fbeta = FBeta(
          metric="recall",
          average="macro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("recall_macro", fbeta.__name__)
      fbeta = FBeta(
          metric="recall",
          average="micro",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("recall_micro", fbeta.__name__)
      fbeta = FBeta(
          metric="recall",
          average=0,
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("recall_0", fbeta.__name__)
      fbeta = FBeta(
          metric="fscore",
          average="macro",
          names="f",
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual("f", fbeta.__name__)
      fbeta = FBeta(
          average="macro",
          names=["f", "p", "r"],
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual(["f", "p", "r"], fbeta.__name__)
      fbeta = FBeta(
          average="binary", make_deterministic=self.make_deterministic
      )
      self.assertEqual(
          ["fscore_binary_1", "precision_binary_1", "recall_binary_1"],
          fbeta.__name__,
      )
      fbeta = FBeta(
          average="binary",
          pos_label=0,
          make_deterministic=self.make_deterministic,
      )
      self.assertEqual(
          ["fscore_binary_0", "precision_binary_0", "recall_binary_0"],
          fbeta.__name__,
      )
  
imports: from unittest import TestCase
  import numpy
  import torch
  import torch.nn
  from poutyne import F1, BinaryF1, FBeta, Model
label_desc: Use image node_id 16 for calling the BaseFBetaTest obj's underlying member method code with example usage: obj.test_names() without return types