Fix kaiser_window for lower precision data types on CPU (#117345)

Fixes #117230.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/117345
Approved by: https://github.com/jgong5, https://github.com/soumith

test/test_tensor_creation_ops.py

@@ -2737,10 +2737,22 @@ class TestTensorCreation(TestCase):
             return
         for size in [0, 1, 2, 5, 10, 50, 100, 1024, 2048]:
             for periodic in [True, False]:
-                res = torch_method(size, periodic=periodic, **kwargs, device=device, dtype=dtype)
+                res = torch_method(
+                    size,
+                    periodic=periodic,
+                    layout=torch.strided,
+                    requires_grad=False,
+                    **kwargs,
+                    device=device,
+                    dtype=dtype,
+                )
                 # NB: scipy always returns a float64 result
-                ref = torch.from_numpy(signal.get_window((name, *(kwargs.values())), size, fftbins=periodic))
-                self.assertEqual(res, ref, exact_dtype=False)
+                ref = torch.from_numpy(
+                    signal.get_window(
+                        (name, *(kwargs.values())), size, fftbins=periodic
+                    )
+                )
+                self.assertEqual(res, ref.to(dtype))
         with self.assertRaisesRegex(RuntimeError, r'not implemented for sparse types'):
             torch_method(3, layout=torch.sparse_coo)
         self.assertTrue(torch_method(3, requires_grad=True).requires_grad)
@@ -2761,7 +2773,7 @@ class TestTensorCreation(TestCase):
     @unittest.skipIf(not TEST_SCIPY, "Scipy not found")
     @skipIfTorchDynamo("TorchDynamo fails with unknown reason")
     @dtypesIfCUDA(torch.float, torch.double, torch.bfloat16, torch.half, torch.long)
-    @dtypes(torch.float, torch.double, torch.long)
+    @dtypes(torch.float, torch.double, torch.long, torch.bfloat16, torch.float16)
     def test_kaiser_window(self, device, dtype):
         for num_test in range(50):
             self._test_signal_window_functions('kaiser', dtype, device, beta=random.random() * 30)