[pir] fix frexp datatype (#61087)

* Update math.py * add test in pir
PaddlePaddle · Jan 25, 2024 · 4f53595 · 4f53595
1 parent cf649d7
commit 4f53595
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Showing 3 changed files with 16 additions and 9 deletions.
diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py
@@ -6547,7 +6547,12 @@ def frexp(x, name=None):
             Tensor(shape=[1, 4], dtype=float32, place=Place(cpu), stop_gradient=True,
             [[1., 2., 2., 3.]])
     """
-    if x.dtype not in [paddle.float32, paddle.float64]:
+    if x.dtype not in [
+        paddle.float32,
+        paddle.float64,
+        DataType.FLOAT32,
+        DataType.FLOAT64,
+    ]:
         raise TypeError(
             f"The data type of input must be one of ['float32', 'float64'], but got {x.dtype}"
         )

diff --git a/test/legacy_test/test_frexp_api.py b/test/legacy_test/test_frexp_api.py
@@ -17,6 +17,7 @@
 
 import paddle
 import paddle.base
+from paddle.pir_utils import test_with_pir_api
 
 
 class TestFrexpAPI(unittest.TestCase):
@@ -35,6 +36,7 @@ def set_input(self):
         self.x_np = np.random.uniform(-3, 3, [10, 12]).astype('float32')
 
     # 静态图单测
+    @test_with_pir_api
     def test_static_api(self):
         # 开启静态图模式
         paddle.enable_static()

diff --git a/test/legacy_test/test_smooth_l1_loss.py b/test/legacy_test/test_smooth_l1_loss.py
@@ -57,7 +57,7 @@ def test_smooth_l1_loss_mean(self):
         expected = smooth_l1_loss_np(input_np, label_np, reduction='mean')
 
         @test_with_pir_api
-        def test_dynamic_or_pir_mode():
+        def test_static():
             prog = paddle.static.Program()
             startup_prog = paddle.static.Program()
             with paddle.static.program_guard(prog, startup_prog):
@@ -90,7 +90,7 @@ def test_dynamic_or_pir_mode():
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
 
-        test_dynamic_or_pir_mode()
+        test_static()
         np.testing.assert_allclose(dy_ret_value, expected, rtol=1e-05)
 
     def test_smooth_l1_loss_sum(self):
@@ -105,7 +105,7 @@ def test_smooth_l1_loss_sum(self):
         expected = smooth_l1_loss_np(input_np, label_np, reduction='sum')
 
         @test_with_pir_api
-        def test_dynamic_or_pir_mode():
+        def test_static():
             prog = paddle.static.Program()
             startup_prog = paddle.static.Program()
             with paddle.static.program_guard(prog, startup_prog):
@@ -138,7 +138,7 @@ def test_dynamic_or_pir_mode():
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
 
-        test_dynamic_or_pir_mode()
+        test_static()
         np.testing.assert_allclose(dy_ret_value, expected, rtol=1e-05)
 
     def test_smooth_l1_loss_none(self):
@@ -153,7 +153,7 @@ def test_smooth_l1_loss_none(self):
         expected = smooth_l1_loss_np(input_np, label_np, reduction='none')
 
         @test_with_pir_api
-        def test_dynamic_or_pir_mode():
+        def test_static():
             prog = paddle.static.Program()
             startup_prog = paddle.static.Program()
             with paddle.static.program_guard(prog, startup_prog):
@@ -186,7 +186,7 @@ def test_dynamic_or_pir_mode():
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
 
-        test_dynamic_or_pir_mode()
+        test_static()
         np.testing.assert_allclose(dy_ret_value, expected, rtol=1e-05)
 
     def test_smooth_l1_loss_delta(self):
@@ -202,7 +202,7 @@ def test_smooth_l1_loss_delta(self):
         expected = smooth_l1_loss_np(input_np, label_np, delta=delta)
 
         @test_with_pir_api
-        def test_dynamic_or_pir_mode():
+        def test_static():
             prog = paddle.static.Program()
             startup_prog = paddle.static.Program()
             with paddle.static.program_guard(prog, startup_prog):
@@ -235,7 +235,7 @@ def test_dynamic_or_pir_mode():
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
 
-        test_dynamic_or_pir_mode()
+        test_static()
         np.testing.assert_allclose(dy_ret_value, expected, rtol=1e-05)