fix SENet154_vd name (#3255)

* fix SENet154_vd name

PaddleCV/image_classification/README.md

@@ -250,7 +250,7 @@ As the activation function ```swish``` and ```relu6``` which separately used in
 |- |:-: |:-: |:-: |
 |[SE_ResNeXt50_32x4d](https://paddle-imagenet-models-name.bj.bcebos.com/SE_ResNeXt50_32x4d_pretrained.tar) | 78.44%/93.96% | 14.916 | 12.126 |
 |[SE_ResNeXt101_32x4d](https://paddle-imagenet-models-name.bj.bcebos.com/SE_ResNeXt101_32x4d_pretrained.tar) | 79.12%/94.20% | 30.085 | 24.110 |
-|[SENet154_vd](https://paddle-imagenet-models-name.bj.bcebos.com/SE154_vd_pretrained.tar) | 81.40%/95.48% | 71.892 | 64.855 |
+|[SENet154_vd](https://paddle-imagenet-models-name.bj.bcebos.com/SENet154_vd_pretrained.tar) | 81.40%/95.48% | 71.892 | 64.855 |
 
 ### Inception
 |model | top-1/top-5 accuracy(CV2) | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) |

PaddleCV/image_classification/README_cn.md

@@ -240,7 +240,7 @@ python infer.py \
 |- |:-: |:-: |:-: |
 |[SE_ResNeXt50_32x4d](https://paddle-imagenet-models-name.bj.bcebos.com/SE_ResNeXt50_32x4d_pretrained.tar) | 78.44%/93.96% | 14.916 | 12.126 |
 |[SE_ResNeXt101_32x4d](https://paddle-imagenet-models-name.bj.bcebos.com/SE_ResNeXt101_32x4d_pretrained.tar) | 79.12%/94.20% | 30.085 | 24.110 |
-|[SENet154_vd](https://paddle-imagenet-models-name.bj.bcebos.com/SE154_vd_pretrained.tar) | 81.40%/95.48% | 71.892 | 64.855 |
+|[SENet154_vd](https://paddle-imagenet-models-name.bj.bcebos.com/SENet154_vd_pretrained.tar) | 81.40%/95.48% | 71.892 | 64.855 |
 
 ### Inception
 |model | top-1/top-5 accuracy(CV2) | Paddle Fluid inference time(ms) | Paddle TensorRT inference time(ms) |

PaddleCV/image_classification/models/__init__.py

@@ -11,7 +11,7 @@ from .resnext_vd import ResNeXt50_vd_64x4d, ResNeXt101_vd_64x4d, ResNeXt152_vd_6
 from .resnet_dist import DistResNet
 from .inception_v4 import InceptionV4
 from .se_resnext import SE_ResNeXt50_32x4d, SE_ResNeXt101_32x4d, SE_ResNeXt152_32x4d
-from .se_resnext_vd import SE_ResNeXt50_32x4d_vd, SE_ResNeXt101_32x4d_vd, SE154_vd
+from .se_resnext_vd import SE_ResNeXt50_32x4d_vd, SE_ResNeXt101_32x4d_vd, SENet154_vd
 from .dpn import DPN68, DPN92, DPN98, DPN107, DPN131
 from .shufflenet_v2_swish import ShuffleNetV2, ShuffleNetV2_x0_5_swish, ShuffleNetV2_x1_0_swish, ShuffleNetV2_x1_5_swish, ShuffleNetV2_x2_0_swish
 from .shufflenet_v2 import ShuffleNetV2_x0_25, ShuffleNetV2_x0_33, ShuffleNetV2_x0_5, ShuffleNetV2_x1_0, ShuffleNetV2_x1_5, ShuffleNetV2_x2_0

PaddleCV/image_classification/models/se_resnext_vd.py

@@ -24,7 +24,7 @@ from paddle.fluid.param_attr import ParamAttr
 
 __all__ = [
     "SE_ResNeXt", "SE_ResNeXt50_32x4d_vd", "SE_ResNeXt101_32x4d_vd",
-    "SE154_vd"
+    "SENet154_vd"
 ]
 
 train_parameters = {
@@ -267,6 +267,6 @@ def SE_ResNeXt101_32x4d_vd():
     return model
 
 
-def SE154_vd():
+def SENet154_vd(): 
     model = SE_ResNeXt(layers=152)
     return model