old_contents: """Tests for module Unbalanced OT with entropy regularization"""
  
  # Author: Hicham Janati <hicham.janati@inria.fr>
  #
  # License: MIT License
  
  import numpy as np
  import ot
  import pytest
  
  
  @pytest.mark.parametrize("metric", ["sinkhorn"])
  def test_unbalanced_convergence(method):
      # test generalized sinkhorn for unbalanced OT
      n = 100
      rng = np.random.RandomState(42)
  
      x = rng.randn(n, 2)
      a = ot.utils.unif(n)
  
      # make dists unbalanced
      b = ot.utils.unif(n) * 1.5
  
      M = ot.dist(x, x)
      epsilon = 1.
      alpha = 1.
      K = np.exp(- M / epsilon)
  
      G, log = ot.unbalanced.sinkhorn_unbalanced(a, b, M, reg=epsilon, alpha=alpha,
                                                 stopThr=1e-10, method=method,
                                                 log=True)
  
      # check fixed point equations
      fi = alpha / (alpha + epsilon)
      v_final = (b / K.T.dot(log["u"])) ** fi
      u_final = (a / K.dot(log["v"])) ** fi
  
      np.testing.assert_allclose(
          u_final, log["u"], atol=1e-05)
      np.testing.assert_allclose(
          v_final, log["v"], atol=1e-05)
  
new_contents: """Tests for module Unbalanced OT with entropy regularization"""
  
  # Author: Hicham Janati <hicham.janati@inria.fr>
  #
  # License: MIT License
  
  import numpy as np
  import ot
  import pytest
  
  
  @pytest.mark.parametrize("method", ["sinkhorn"])
  def test_unbalanced_convergence(method):
      # test generalized sinkhorn for unbalanced OT
      n = 100
      rng = np.random.RandomState(42)
  
      x = rng.randn(n, 2)
      a = ot.utils.unif(n)
  
      # make dists unbalanced
      b = ot.utils.unif(n) * 1.5
  
      M = ot.dist(x, x)
      epsilon = 1.
      alpha = 1.
      K = np.exp(- M / epsilon)
  
      G, log = ot.unbalanced.sinkhorn_unbalanced(a, b, M, reg=epsilon, alpha=alpha,
                                                 stopThr=1e-10, method=method,
                                                 log=True)
  
      # check fixed point equations
      fi = alpha / (alpha + epsilon)
      v_final = (b / K.T.dot(log["u"])) ** fi
      u_final = (a / K.dot(log["v"])) ** fi
  
      np.testing.assert_allclose(
          u_final, log["u"], atol=1e-05)
      np.testing.assert_allclose(
          v_final, log["v"], atol=1e-05)
  
subject: fix typo in test argument