diff --git a/paddle/fluid/imperative/tracer.cc b/paddle/fluid/imperative/tracer.cc
index 742514c0910a23c99ab5286c23071bfcf2db0385..41ad70e5a5741b78acbf6403bf9cd6b1a390ecf0 100644
--- a/paddle/fluid/imperative/tracer.cc
+++ b/paddle/fluid/imperative/tracer.cc
@@ -84,7 +84,7 @@ paddle::framework::GarbageCollector* Tracer::MutableGarbageCollectorIfNotExists(
   if (gcs_.count(place) == 0) {
     std::unique_ptr<framework::GarbageCollector> gc;
     if (platform::is_gpu_place(place)) {
-#ifdef PADDLE_WITH_CUDA
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
       gc.reset(new framework::DefaultStreamGarbageCollector(
           BOOST_GET_CONST(platform::CUDAPlace, place), 0));
 
@@ -95,7 +95,7 @@ paddle::framework::GarbageCollector* Tracer::MutableGarbageCollectorIfNotExists(
           "Please recompile or reinstall Paddle with GPU support."));
 #endif
     } else if (platform::is_cuda_pinned_place(place)) {
-#ifdef PADDLE_WITH_CUDA
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
       gc.reset(new framework::CUDAPinnedGarbageCollector(
           BOOST_GET_CONST(platform::CUDAPinnedPlace, place), 0));
 
diff --git a/python/paddle/fluid/tests/unittests/test_var_base.py b/python/paddle/fluid/tests/unittests/test_var_base.py
index a65308c84e7193f567e5c17e870e850441daabd0..8bf42390d1ea899b64829e4e109b3f3f56ff6e82 100644
--- a/python/paddle/fluid/tests/unittests/test_var_base.py
+++ b/python/paddle/fluid/tests/unittests/test_var_base.py
@@ -256,19 +256,21 @@ class TestVarBase(unittest.TestCase):
             detach_x = x.detach()
             self.assertTrue(detach_x.stop_gradient, True)
 
+            cmp_float = np.allclose if core.is_compiled_with_rocm(
+            ) else np.array_equal
             detach_x[:] = 10.0
-            self.assertTrue(np.array_equal(x.numpy(), [10.0]))
+            self.assertTrue(cmp_float(x.numpy(), [10.0]))
 
             y = x**2
             y.backward()
-            self.assertTrue(np.array_equal(x.grad.numpy(), [20.0]))
+            self.assertTrue(cmp_float(x.grad.numpy(), [20.0]))
             self.assertEqual(detach_x.grad, None)
 
             detach_x.stop_gradient = False  # Set stop_gradient to be False, supported auto-grad
             z = 3 * detach_x**2
             z.backward()
-            self.assertTrue(np.array_equal(x.grad.numpy(), [20.0]))
-            self.assertTrue(np.array_equal(detach_x.grad.numpy(), [60.0]))
+            self.assertTrue(cmp_float(x.grad.numpy(), [20.0]))
+            self.assertTrue(cmp_float(detach_x.grad.numpy(), [60.0]))
 
             # Due to sharing of data with origin Tensor, There are some unsafe operations:
             with self.assertRaises(RuntimeError):