add the check for bfloat16 dtype

python/paddle/tensor/math.py

@@ -4496,9 +4496,9 @@ def lerp(x, y, weight, name=None):
             lerp(x, y, weight) = x + weight * (y - x).
 
     Args:
-        x (Tensor): An N-D Tensor with starting points, the data type is float16, float32, float64.
-        y (Tensor): An N-D Tensor with ending points, the data type is float16, float32, float64.
-        weight (float|Tensor): The weight for the interpolation formula. When weight is Tensor, the data type is float16, float32, float64.
+        x (Tensor): An N-D Tensor with starting points, the data type is bfloat16, float16, float32, float64.
+        y (Tensor): An N-D Tensor with ending points, the data type is bfloat16, float16, float32, float64.
+        weight (float|Tensor): The weight for the interpolation formula. When weight is Tensor, the data type is bfloat16, float16, float32, float64.
         name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
     Returns:
@@ -4523,13 +4523,16 @@ def lerp(x, y, weight, name=None):
         return _C_ops.lerp(x, y, weight)
     else:
         check_variable_and_dtype(
-            x, 'x', ['float16', 'float32', 'float64'], 'lerp'
+            x, 'x', ['uint16', 'float16', 'float32', 'float64'], 'lerp'
         )
         check_variable_and_dtype(
-            y, 'y', ['float16', 'float32', 'float64'], 'lerp'
+            y, 'y', ['uint16', 'float16', 'float32', 'float64'], 'lerp'
         )
         check_variable_and_dtype(
-            weight, 'weight', ['float16', 'float32', 'float64'], 'lerp'
+            weight,
+            'weight',
+            ['uint16', 'float16', 'float32', 'float64'],
+            'lerp',
         )
 
         helper = LayerHelper('lerp', **locals())