[PIR] A-13 Adapt expand test_errors (#62849)

ooooo-create · web-flow · commit 6b3f90e5646f · 2024-03-25T14:11:39.000+08:00
diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py
@@ -4180,7 +4180,7 @@ def broadcast_to(x, shape, name=None):
 
 
     Args:
-        x (Tensor): The input tensor, its data type is bool, float16, float32, float64, int32 or int64.
+        x (Tensor): The input tensor, its data type is bool, float16, float32, float64, int32, int64, uint8 or uint16.
         shape (list|tuple|Tensor): The result shape after broadcasting. The data type is int32. If shape is a list or tuple, all its elements
             should be integers or 0-D or 1-D Tensors with the data type int32. If shape is a Tensor, it should be an 1-D Tensor with the data type int32.
             The value -1 in shape means keeping the corresponding dimension unchanged.
@@ -4211,7 +4211,7 @@ def expand(x, shape, name=None):
     Both the number of dimensions of ``x`` and the number of elements in ``shape`` should be less than or equal to 6. And the number of dimensions of ``x`` should be less than the number of elements in ``shape``. The dimension to expand must have a value 0.
 
     Args:
-        x (Tensor): The input Tensor, its data type is bool, float32, float64, int32 or int64.
+        x (Tensor): The input Tensor, its data type is bool, float16, float32, float64, int32, int64, uint8 or uint16.
         shape (list|tuple|Tensor): The result shape after expanding. The data type is int32. If shape is a list or tuple, all its elements
             should be integers or 0-D or 1-D Tensors with the data type int32. If shape is a Tensor, it should be an 1-D Tensor with the data type int32.
             The value -1 in shape means keeping the corresponding dimension unchanged.
@@ -4248,7 +4248,7 @@ def expand(x, shape, name=None):
             if paddle.utils._contain_var(shape):
                 shape = paddle.utils.get_int_tensor_list(shape)
         else:
-            TypeError("Shape only supports OpResult, or list, or tuple.")
+            raise TypeError("Shape only supports Value, or list, or tuple.")
         return _C_ops.expand(x, shape)
     else:
         if isinstance(shape, Variable):
@@ -4275,6 +4275,7 @@ def expand(x, shape, name=None):
                 'float64',
                 'int32',
                 'int64',
+                'uint8',
                 'uint16',
             ],
             'expand',
diff --git a/test/legacy_test/test_broadcast_to_op.py b/test/legacy_test/test_broadcast_to_op.py
@@ -18,25 +18,31 @@
 
 import paddle
 from paddle import base
+from paddle.framework import in_pir_mode
 from paddle.pir_utils import test_with_pir_api
-from paddle.static import Program, program_guard
 
 paddle.enable_static()
 
 
 class TestBroadcastToError(unittest.TestCase):
+    @test_with_pir_api
     def test_errors(self):
-        with program_guard(Program(), Program()):
-            x1 = base.create_lod_tensor(
-                np.array([[-1]]), [[1]], base.CPUPlace()
-            )
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             shape = [2, 2]
-            self.assertRaises(TypeError, paddle.tensor.broadcast_to, x1, shape)
-            x2 = paddle.static.data(name='x2', shape=[-1, 4], dtype="uint8")
-            self.assertRaises(TypeError, paddle.tensor.broadcast_to, x2, shape)
-            x3 = paddle.static.data(name='x3', shape=[-1, 4], dtype="bool")
-            x3.stop_gradient = False
-            self.assertRaises(ValueError, paddle.tensor.broadcast_to, x3, shape)
+            if not in_pir_mode():
+                x1 = base.create_lod_tensor(
+                    np.array([[-1]]), [[1]], base.CPUPlace()
+                )
+                self.assertRaises(
+                    TypeError, paddle.tensor.broadcast_to, x1, shape
+                )
+            x2 = paddle.static.data(name='x2', shape=[-1, 4], dtype="bool")
+            x2.stop_gradient = False
+            self.assertRaises(ValueError, paddle.tensor.broadcast_to, x2, shape)
+            x2.stop_gradient = True
+            self.assertRaises(TypeError, paddle.tensor.broadcast_to, x2, 1)
 
 
 # Test python API
diff --git a/test/legacy_test/test_expand_v2_op.py b/test/legacy_test/test_expand_v2_op.py
@@ -23,6 +23,7 @@
 import paddle
 from paddle import base
 from paddle.base import Program, core, program_guard
+from paddle.framework import in_pir_mode
 from paddle.pir_utils import test_with_pir_api
 
 
@@ -297,19 +298,23 @@ def test_check_grad(self):
 
 
 class TestExpandV2Error(unittest.TestCase):
+    @test_with_pir_api
     def test_errors(self):
         paddle.enable_static()
-        with program_guard(Program(), Program()):
-            x1 = base.create_lod_tensor(
-                np.array([[-1]]), [[1]], base.CPUPlace()
-            )
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             shape = [2, 2]
-            self.assertRaises(TypeError, paddle.tensor.expand, x1, shape)
-            x2 = paddle.static.data(name='x2', shape=[-1, 4], dtype="uint8")
-            self.assertRaises(TypeError, paddle.tensor.expand, x2, shape)
-            x3 = paddle.static.data(name='x3', shape=[-1, 4], dtype="bool")
-            x3.stop_gradient = False
-            self.assertRaises(ValueError, paddle.tensor.expand, x3, shape)
+            if not in_pir_mode():
+                x1 = base.create_lod_tensor(
+                    np.array([[-1]]), [[1]], base.CPUPlace()
+                )
+                self.assertRaises(TypeError, paddle.tensor.expand, x1, shape)
+            x2 = paddle.static.data(name='x2', shape=[-1, 4], dtype="bool")
+            x2.stop_gradient = False
+            self.assertRaises(ValueError, paddle.tensor.expand, x2, shape)
+            x2.stop_gradient = True
+            self.assertRaises(TypeError, paddle.tensor.expand, x2, 1)
         paddle.disable_static()
 
 
