diff --git a/test/test_mps.py b/test/test_mps.py
index c89a9d2..03410e2 100644
--- a/test/test_mps.py
+++ b/test/test_mps.py
@@ -65,7 +65,7 @@
         return np.maximum(np_features, np.zeros(np_features.shape)).astype(np_features.dtype)
 
     def testNpRelu(self):
-        torch.testing.assert_allclose(
+        torch.testing.assert_close(
             np.array([[0., 0.7, 0.0, 0.3, 0.0], [0.1, 0.0, 0.5, 0.0, 0.9]]),
             self._npRelu(
                 np.array([[-0.9, 0.7, -0.5, 0.3, -0.1], [0.1, -0.3, 0.5, -0.7,
@@ -79,7 +79,7 @@
         py_relu = torch.nn.ReLU(inplace=False)(py_tensor)
         py_relu_cpu = py_relu.to("cpu")
 
-        torch.testing.assert_allclose(np_relu, py_relu_cpu)
+        self.assertEqual(np_relu, py_relu_cpu)
 
     def _testReluInPlace(self, np_features, device):
         np_relu = self._npRelu(np_features)
@@ -89,9 +89,9 @@
         py_relu = torch.nn.ReLU(inplace=True)(py_tensor)
         py_relu_cpu = py_relu.to("cpu")
 
-        torch.testing.assert_allclose(np_relu, py_relu_cpu)
+        self.assertEqual(np_relu, py_relu_cpu)
         # Inplace Relu modifies the initial input and it should match the output of Relu
-        torch.testing.assert_allclose(np_relu, py_tensor.to("cpu"))
+        self.assertEqual(np_relu, py_tensor.to("cpu"))
 
     def testNumbersCPU(self):
         for t in [np.int32]:
@@ -156,7 +156,7 @@
         return np.maximum(np_features, negative_slope * np_features).astype(np_features.dtype)
 
     def testNpLeakyRelu(self):
-        torch.testing.assert_allclose(
+        torch.testing.assert_close(
             np.array([[-0.09, 0.7, -0.05, 0.3, -0.01],
                       [0.1, -0.03, 0.5, -0.07, 0.9]]),
             self._npLeakyRelu(
@@ -171,14 +171,14 @@
 
         cpu_leaky_relu = relu_op(cpu_x)
         mps_leaky_relu = relu_op(mps_x)
-        torch.testing.assert_allclose(cpu_leaky_relu, mps_leaky_relu.to('cpu'))
+        torch.testing.assert_close(cpu_leaky_relu, mps_leaky_relu.to('cpu'))
 
         # test backward pass
         cpu_grad = torch.ones_like(cpu_leaky_relu)
         mps_grad = cpu_grad.to('mps')
         cpu_leaky_relu.backward(gradient=cpu_grad)
         mps_leaky_relu.backward(gradient=mps_grad)
-        torch.testing.assert_allclose(cpu_x.grad, mps_x.grad.to('cpu'))
+        torch.testing.assert_close(cpu_x.grad, mps_x.grad.to('cpu'))
 
     def testNumbersCPU(self):
         for t in [np.float32]:
@@ -257,14 +257,14 @@
 
         cpu_leaky_relu = relu_op(cpu_x)
         mps_leaky_relu = relu_op(mps_x)
-        torch.testing.assert_allclose(cpu_leaky_relu, mps_leaky_relu.to('cpu'))
+        torch.testing.assert_close(cpu_leaky_relu, mps_leaky_relu.to('cpu'))
 
         # test backward pass
         cpu_grad = torch.ones_like(cpu_leaky_relu)
         mps_grad = cpu_grad.to('mps')
         cpu_leaky_relu.backward(gradient=cpu_grad)
         mps_leaky_relu.backward(gradient=mps_grad)
-        torch.testing.assert_allclose(cpu_x.grad, mps_x.grad.to('cpu'))
+        torch.testing.assert_close(cpu_x.grad, mps_x.grad.to('cpu'))
 
     def testNumbersGPU(self):
         for t in [np.float32]:
@@ -293,14 +293,14 @@
         B = torch.ones(5, 6).to("mps")
         C = torch.ones(6, 5).to("mps")
         D = torch.mm(B, C).cpu()
-        torch.testing.assert_allclose(D, torch.full((5, 5), 6.0))
+        torch.testing.assert_close(D, torch.full((5, 5), 6.0))
 
     def test_addmm(self):
         A = torch.ones(5, 5).to("mps")
         B = torch.ones(5, 6).to("mps")
         C = torch.ones(6, 5).to("mps")
         D = torch.addmm(A, B, C).to("cpu")
-        torch.testing.assert_allclose(D, torch.full((5, 5), 7.0))
+        torch.testing.assert_close(D, torch.full((5, 5), 7.0))
 
     def test_bmm(self):
         batch1_cpu = torch.randn(10, 3, 4)
@@ -355,7 +355,7 @@
     def test_local_scalar_dense_mps(self):
         x_cpu = torch.randn(1)
         y_mps = x_cpu.to("mps")
-        torch.testing.assert_allclose(x_cpu.item(), y_mps.item())
+        torch.testing.assert_close(x_cpu.item(), y_mps.item())
 
     def test_linear_1d_weight(self):
         device = 'cpu'