add `uint8` when check_dtype in assign (#33157)

* fix uint8 check in assign

* fix assign unittests

* fix xpu test_assign

python/paddle/fluid/layers/tensor.py

@@ -587,7 +587,8 @@ def assign(input, output=None):
     # after this api.
     if isinstance(input, (Variable, core.VarBase)):
         check_dtype(input.dtype, 'input', [
-            'float16', 'uint16', 'float32', 'float64', 'int32', 'int64', 'bool'
+            'float16', 'uint16', 'float32', 'float64', 'int32', 'int64',
+            'uint8', 'bool'
         ], 'assign', '(When the type of input in assign is Variable.)')
         if output is None:
             output = helper.create_variable_for_type_inference(

python/paddle/fluid/tests/unittests/test_assign_op.py

@@ -90,12 +90,9 @@ class TestAssignOpError(unittest.TestCase):
             x1 = fluid.create_lod_tensor(
                 np.array([[-1]]), [[1]], fluid.CPUPlace())
             self.assertRaises(TypeError, fluid.layers.assign, x1)
-            # When the type of input is Variable, the dtype of input must be float16, float32, float64, int32, int64, bool.
-            x3 = fluid.layers.data(name='x3', shape=[4], dtype="uint8")
-            self.assertRaises(TypeError, fluid.layers.assign, x3)
             # When the type of input is numpy.ndarray, the dtype of input must be float32, int32.
-            x4 = np.array([[2.5, 2.5]], dtype='uint8')
-            self.assertRaises(TypeError, fluid.layers.assign, x4)
+            x2 = np.array([[2.5, 2.5]], dtype='uint8')
+            self.assertRaises(TypeError, fluid.layers.assign, x2)
 
 
 class TestAssignOApi(unittest.TestCase):
@@ -180,12 +177,9 @@ class TestAssignOpErrorApi(unittest.TestCase):
             x1 = fluid.create_lod_tensor(
                 np.array([[-1]]), [[1]], fluid.CPUPlace())
             self.assertRaises(TypeError, paddle.assign, x1)
-            # When the type of input is Variable, the dtype of input must be float16, float32, float64, int32, int64, bool.
-            x3 = fluid.layers.data(name='x3', shape=[4], dtype="uint8")
-            self.assertRaises(TypeError, paddle.assign, x3)
             # When the type of input is numpy.ndarray, the dtype of input must be float32, int32.
-            x4 = np.array([[2.5, 2.5]], dtype='uint8')
-            self.assertRaises(TypeError, paddle.assign, x4)
+            x2 = np.array([[2.5, 2.5]], dtype='uint8')
+            self.assertRaises(TypeError, paddle.assign, x2)
 
 
 if __name__ == '__main__':

python/paddle/fluid/tests/unittests/xpu/test_assign_op_xpu.py

@@ -82,11 +82,8 @@ class TestAssignOpError(unittest.TestCase):
             x1 = fluid.create_lod_tensor(
                 np.array([[-1]]), [[1]], fluid.XPUPlace(0))
             self.assertRaises(TypeError, fluid.layers.assign, x1)
-            # When the type of input is Variable, the dtype of input must be float16, float32, float64, int32, int64, bool.
-            x3 = fluid.layers.data(name='x3', shape=[4], dtype="uint8")
-            self.assertRaises(TypeError, fluid.layers.assign, x3)
-            x4 = np.array([[2.5, 2.5]], dtype='uint8')
-            self.assertRaises(TypeError, fluid.layers.assign, x4)
+            x2 = np.array([[2.5, 2.5]], dtype='uint8')
+            self.assertRaises(TypeError, fluid.layers.assign, x2)
 
 
 if __name__ == '__main__':