[BE] Use assertEqual in MultiKernel tests (pytorch#127725)

Pull Request resolved: pytorch#127725
Approved by: https://github.com/lezcano
ghstack dependencies: pytorch#131044, pytorch#127724

test/inductor/test_multi_kernel.py

@@ -83,7 +83,7 @@ def test_softmax(self, expect_multi_kernel=True):
         # One for the first pass and one for the second pass.
         # We mainly care about the wrapper for the final pass here.
         wrapper_code = wrapper_code[-1]
-        self.assertTrue(torch.allclose(ref, act))
+        self.assertEqual(ref, act)
         if expect_multi_kernel:
             self.assertTrue(_contains_multi_kernel_code(wrapper_code))
         else:
@@ -142,9 +142,7 @@ def test_layernorm(self):
         x = torch.rand(2, 1024).cuda()
         ref = ln(x)
         act = torch.compile(ln)(x)
-        self.assertTrue(
-            torch.allclose(ref, act, atol=1e-4, rtol=1e-4), f"ref:\n{ref}\nact:\n{act}"
-        )
+        self.assertEqual(ref, act, atol=1e-4, rtol=1e-4)
 
     def test_inplace_update(self):
         """
@@ -158,7 +156,7 @@ def f(x, y):
         y = torch.rand(1024, 1024).cuda()
         ref = f(x, y)
         act = torch.compile(f)(x, y)
-        self.assertTrue(torch.allclose(ref, act))
+        self.assertEqual(ref, act)
 
     def test_transformer_snippet(self):
         model = TransformerSnippet().cuda()
@@ -179,10 +177,7 @@ def f(*x):
         # inductor random number implementation is different to eager.
         # We should fallback to eager if we want to test accuracy.
         if config.fallback_random:
-            self.assertTrue(
-                torch.allclose(ref, act, atol=1e-4, rtol=1e-4),
-                f"ref:\n{ref}\nact:\n{act}",
-            )
+            self.assertEqual(ref, act, atol=1e-4, rtol=1e-4)
 
     def test_transformer_snippet_with_fallback_random(self):
         """
@@ -236,7 +231,7 @@ def f(x, y):
 
         ref = f(x, y_ref)
         act = torch.compile(f)(x, y)
-        self.assertTrue(torch.allclose(y_ref, y))
+        self.assertEqual(y_ref, y)
 
     def test_reduction_scratch_buffer(self, force_multi_kernel=1):
         """
@@ -261,7 +256,7 @@ def f(x):
         ref = f(x)
         with config.patch("triton.multi_kernel", force_multi_kernel):
             act = torch.compile(f)(x)
-        self.assertTrue(torch.allclose(ref, act))
+        self.assertEqual(ref, act)
 
     def test_split_scan(self, force_multi_kernel=1):
         def f(x):