[PIR] D-18 Adapt randint test_errors

python/paddle/base/data_feeder.py

@@ -229,18 +229,22 @@ def check_dtype(
 def check_shape(
     shape,
     op_name,
-    expected_shape_type=(list, tuple, Variable),
-    expected_element_type=(int, Variable),
+    expected_shape_type=(list, tuple, Variable, Value),
+    expected_element_type=(int, Variable, Value),
     expected_tensor_dtype=('int32', 'int64'),
 ):
     # See NOTE [ Why skip dynamic graph check ]
     if in_dygraph_mode():
         return
     check_type(shape, 'shape', expected_shape_type, op_name)
-    if expected_element_type is not None and not isinstance(shape, Variable):
+    if expected_element_type is not None and not isinstance(
+        shape, (Variable, Value)
+    ):
         for item in shape:
             check_type(item, 'element of shape', expected_element_type, op_name)
-            if expected_tensor_dtype is not None and isinstance(item, Variable):
+            if expected_tensor_dtype is not None and isinstance(
+                item, (Variable, Value)
+            ):
                 check_dtype(
                     item.dtype,
                     'element of shape',
@@ -250,7 +254,9 @@ def check_shape(
                         ', '.join(expected_tensor_dtype)
                     ),
                 )
-    if expected_tensor_dtype is not None and isinstance(shape, Variable):
+    if expected_tensor_dtype is not None and isinstance(
+        shape, (Variable, Value)
+    ):
         check_dtype(shape.dtype, 'shape', expected_tensor_dtype, op_name)
 
 

python/paddle/tensor/random.py

@@ -1112,7 +1112,7 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
             low, high, shape, dtype, _current_expected_place()
         )
     elif in_pir_mode():
-        check_type(shape, 'shape', (list, tuple, paddle.pir.Value), 'randint')
+        check_shape(shape, 'randint')
         check_dtype(dtype, 'dtype', ['int32', 'int64'], 'randint')
         if paddle.utils._contain_var(shape):
             shape = paddle.utils.get_int_tensor_list(

test/legacy_test/test_randint_op.py

@@ -18,9 +18,8 @@
 from op_test import OpTest
 
 import paddle
-from paddle import base
 from paddle.base import core
-from paddle.static import Program, program_guard
+from paddle.pir_utils import test_with_pir_api
 
 paddle.enable_static()
 
@@ -54,8 +53,11 @@ def verify_output(self, outs):
 
 
 class TestRandintOpError(unittest.TestCase):
+    @test_with_pir_api
     def test_errors(self):
-        with program_guard(Program(), Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             self.assertRaises(TypeError, paddle.randint, 5, shape=np.array([2]))
             self.assertRaises(TypeError, paddle.randint, 5, dtype='float32')
             self.assertRaises(ValueError, paddle.randint, 5, 5)
@@ -67,14 +69,6 @@ def test_errors(self):
                 TypeError, paddle.randint, 5, shape=[shape_tensor]
             )
 
-    def test_pir_error(self):
-        with paddle.pir_utils.IrGuard():
-            self.assertRaises(TypeError, paddle.randint, 5, shape=np.array([2]))
-            self.assertRaises(TypeError, paddle.randint, 5, dtype='float32')
-            self.assertRaises(ValueError, paddle.randint, 5, 5)
-            self.assertRaises(ValueError, paddle.randint, -5)
-            self.assertRaises(TypeError, paddle.randint, 5, shape=['2'])
-
 
 class TestRandintOp_attr_tensorlist(OpTest):
     def setUp(self):
@@ -125,7 +119,9 @@ def verify_output(self, outs):
 # Test python API
 class TestRandintAPI(unittest.TestCase):
     def test_api(self):
-        with program_guard(Program(), Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             # results are from [0, 5).
             out1 = paddle.randint(5)
             # shape is a list and dtype is 'int32'
@@ -229,17 +225,20 @@ def test_dygraph(self):
         self.assertEqual(x.shape, [])
         paddle.enable_static()
 
+    @test_with_pir_api
     def test_static(self):
-        with base.program_guard(base.Program(), base.Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             x = paddle.randint(-10, 10, [])
 
             # Test compile shape
-            self.assertEqual(x.shape, ())
+            self.assertEqual(tuple(x.shape), ())
 
             # Test runtime shape
-            exe = base.Executor()
+            exe = paddle.static.Executor()
             result = exe.run(fetch_list=[x])
-            self.assertEqual(result[0].shape, ())
+            self.assertEqual(tuple(result[0].shape), ())
 
         paddle.enable_static()