diff --git a/.github/workflows/tests_full.yml b/.github/workflows/tests_full.yml
index e550c88..0865876 100644
--- a/.github/workflows/tests_full.yml
+++ b/.github/workflows/tests_full.yml
@@ -73,7 +73,7 @@ jobs:
       matrix:
         os: [ windows-2019, ubuntu-18.04, macos-11 ]
         python-version: [ 3.6, 3.7, 3.8, 3.9 ]
-        pytorch-version: [1.8.0, 1.9.0, 1.10.0, 1.11.0, 1.12.0]
+        pytorch-version: [1.8.0, 1.9.0, 1.10.0, 1.11.0, 1.12.0, 1.13.0]
         exclude:
           - python-version: 3.6
             pytorch-version: 1.11.0
diff --git a/example.py b/example.py
index 6de0f36..98ba5b9 100644
--- a/example.py
+++ b/example.py
@@ -83,7 +83,6 @@
 t_ = time.time()
 norm, H, E = tf_normalizer.normalize(I=t_to_transform, stains=True)
 print("tf runtime:", time.time() - t_)
-
 plt.figure()
 plt.suptitle('tensorflow normalizer')
 plt.subplot(2, 2, 1)
diff --git a/torchstain/torch/normalizers/macenko.py b/torchstain/torch/normalizers/macenko.py
index 710b7e3..b04cd28 100644
--- a/torchstain/torch/normalizers/macenko.py
+++ b/torchstain/torch/normalizers/macenko.py
@@ -14,7 +14,8 @@ def __init__(self):
                                    [0.7201, 0.8012],
                                    [0.4062, 0.5581]])
         self.maxCRef = torch.tensor([1.9705, 1.0308])
-
+        self.deprecated_torch = torch.__version__ < (1,9,0)
+        
     def __convert_rgb2od(self, I, Io, beta):
         I = I.permute(1, 2, 0)
 
@@ -49,13 +50,16 @@ def __find_concentration(self, OD, HE):
         Y = OD.T
 
         # determine concentrations of the individual stains
-        return torch.lstsq(Y, HE)[0][:2]
+        if self.deprecated_torch:
+            return torch.lstsq(Y, HE)[0][:2]
+    
+        return torch.linalg.lstsq(HE, Y)[0]
 
     def __compute_matrices(self, I, Io, alpha, beta):
         OD, ODhat = self.__convert_rgb2od(I, Io=Io, beta=beta)
 
         # compute eigenvectors
-        _, eigvecs = torch.symeig(cov(ODhat.T), eigenvectors=True)
+        _, eigvecs = torch.linalg.eigh(cov(ODhat.T)) 
         eigvecs = eigvecs[:, [1, 2]]
 
         HE = self.__find_HE(ODhat, eigvecs, alpha)