diff --git a/ppcls/arch/backbone/model_zoo/convnext.py b/ppcls/arch/backbone/model_zoo/convnext.py
index d089d5e01cc4313a3cf61a1c4f88a6fedae21ce9..8bfa41f4f847592597eb50a3feba8fd8b9a4ddb7 100644
--- a/ppcls/arch/backbone/model_zoo/convnext.py
+++ b/ppcls/arch/backbone/model_zoo/convnext.py
@@ -39,7 +39,7 @@ def drop_path(x, drop_prob=0., training=False):
     """
     if drop_prob == 0. or not training:
         return x
-    keep_prob = paddle.to_tensor(1 - drop_prob)
+    keep_prob = paddle.to_tensor(1 - drop_prob, dtype=x.dtype)
     shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
     random_tensor = keep_prob + paddle.rand(shape, dtype=x.dtype)
     random_tensor = paddle.floor(random_tensor)  # binarize
diff --git a/ppcls/arch/backbone/model_zoo/tnt.py b/ppcls/arch/backbone/model_zoo/tnt.py
index b9d8327098db724d3514987ffac6cb4091753caa..c7bedd9f22e77572f4c46def03bb4026f5ecc24b 100644
--- a/ppcls/arch/backbone/model_zoo/tnt.py
+++ b/ppcls/arch/backbone/model_zoo/tnt.py
@@ -45,7 +45,7 @@ def drop_path(x, drop_prob=0., training=False):
     """
     if drop_prob == 0. or not training:
         return x
-    keep_prob = paddle.to_tensor(1 - drop_prob)
+    keep_prob = paddle.to_tensor(1 - drop_prob, dtype=x.dtype)
     shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
     random_tensor = paddle.add(keep_prob, paddle.rand(shape, dtype=x.dtype))
     random_tensor = paddle.floor(random_tensor)  # binarize
diff --git a/ppcls/arch/backbone/model_zoo/van.py b/ppcls/arch/backbone/model_zoo/van.py
index ea7c88853d249534e4dd108188b3d96ad04ff708..a903981983214d04454ccb60244ab94ef1368632 100644
--- a/ppcls/arch/backbone/model_zoo/van.py
+++ b/ppcls/arch/backbone/model_zoo/van.py
@@ -42,7 +42,7 @@ def drop_path(x, drop_prob=0., training=False):
     """
     if drop_prob == 0. or not training:
         return x
-    keep_prob = paddle.to_tensor(1 - drop_prob)
+    keep_prob = paddle.to_tensor(1 - drop_prob, dtype=x.dtype)
     shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
     random_tensor = keep_prob + paddle.rand(shape, dtype=x.dtype)
     random_tensor = paddle.floor(random_tensor)  # binarize
diff --git a/ppcls/arch/backbone/model_zoo/vision_transformer.py b/ppcls/arch/backbone/model_zoo/vision_transformer.py
index acecf61f1cd7b517a855301b324a7639a6c047ee..fbec1fcb48d75322f36e4c8abd277132d5825b92 100644
--- a/ppcls/arch/backbone/model_zoo/vision_transformer.py
+++ b/ppcls/arch/backbone/model_zoo/vision_transformer.py
@@ -60,7 +60,7 @@ def drop_path(x, drop_prob=0., training=False):
     """
     if drop_prob == 0. or not training:
         return x
-    keep_prob = paddle.to_tensor(1 - drop_prob)
+    keep_prob = paddle.to_tensor(1 - drop_prob, dtype=x.dtype)
     shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
     random_tensor = keep_prob + paddle.rand(shape).astype(x.dtype)
     random_tensor = paddle.floor(random_tensor)  # binarize