diff --git a/python/paddle/vision/models/mobilenetv2.py b/python/paddle/vision/models/mobilenetv2.py
index 60914b48f008f..9122e1cfdb381 100644
--- a/python/paddle/vision/models/mobilenetv2.py
+++ b/python/paddle/vision/models/mobilenetv2.py
@@ -12,6 +12,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import annotations
+
+from typing import (
+    TYPE_CHECKING,
+    TypedDict,
+)
+
+from typing_extensions import NotRequired, Unpack
+
 import paddle
 from paddle import nn
 from paddle.utils.download import get_weights_path_from_url
@@ -19,6 +28,9 @@
 from ..ops import ConvNormActivation
 from ._utils import _make_divisible
 
+if TYPE_CHECKING:
+    from paddle import Tensor
+
 __all__ = []
 
 model_urls = {
@@ -29,10 +41,21 @@
 }
 
 
+class _MobileNetV2Options(TypedDict):
+    scale: NotRequired[float]
+    num_classes: NotRequired[int]
+    with_pool: NotRequired[bool]
+
+
 class InvertedResidual(nn.Layer):
     def __init__(
-        self, inp, oup, stride, expand_ratio, norm_layer=nn.BatchNorm2D
-    ):
+        self,
+        inp: int,
+        oup: int,
+        stride: int,
+        expand_ratio: float,
+        norm_layer: nn.Layer = nn.BatchNorm2D,
+    ) -> None:
         super().__init__()
         self.stride = stride
         assert stride in [1, 2]
@@ -67,7 +90,7 @@ def __init__(
         )
         self.conv = nn.Sequential(*layers)
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         if self.use_res_connect:
             return x + self.conv(x)
         else:
@@ -102,7 +125,12 @@ class MobileNetV2(nn.Layer):
             [1, 1000]
     """
 
-    def __init__(self, scale=1.0, num_classes=1000, with_pool=True):
+    def __init__(
+        self,
+        scale: float = 1.0,
+        num_classes: int = 1000,
+        with_pool: bool = True,
+    ) -> None:
         super().__init__()
         self.num_classes = num_classes
         self.with_pool = with_pool
@@ -171,7 +199,7 @@ def __init__(self, scale=1.0, num_classes=1000, with_pool=True):
                 nn.Dropout(0.2), nn.Linear(self.last_channel, num_classes)
             )
 
-    def forward(self, x):
+    def forward(self, x: Tensor) -> Tensor:
         x = self.features(x)
 
         if self.with_pool:
@@ -183,7 +211,9 @@ def forward(self, x):
         return x
 
 
-def _mobilenet(arch, pretrained=False, **kwargs):
+def _mobilenet(
+    arch: str, pretrained: bool = False, **kwargs: Unpack[_MobileNetV2Options]
+) -> MobileNetV2:
     model = MobileNetV2(**kwargs)
     if pretrained:
         assert (
@@ -199,7 +229,11 @@ def _mobilenet(arch, pretrained=False, **kwargs):
     return model
 
 
-def mobilenet_v2(pretrained=False, scale=1.0, **kwargs):
+def mobilenet_v2(
+    pretrained: bool = False,
+    scale: float = 1.0,
+    **kwargs: Unpack[_MobileNetV2Options],
+) -> MobileNetV2:
     """MobileNetV2 from
     `"MobileNetV2: Inverted Residuals and Linear Bottlenecks" <https://arxiv.org/abs/1801.04381>`_.