modify swinv2

docs/zh_CN/models/ImageNet1k/SwinTransformerV2.md

@@ -72,7 +72,7 @@ SwinTransformerV2 在 SwinTransformer 的基础上进行改进，可处理大尺
 
 ## 3. 模型训练、评估和预测
 
-此部分内容包括训练环境配置、ImageNet数据的准备、SwinTransformer 在 ImageNet 上的训练、评估、预测等内容。在 `ppcls/configs/ImageNet/SwinTransformer/` 中提供了 SwinTransformer 的训练配置，可以通过如下脚本启动训练：此部分内容可以参考[ResNet50 模型训练、评估和预测](./ResNet.md#3)。
+此部分内容包括训练环境配置、ImageNet数据的准备、SwinTransformerV2 在 ImageNet 上的训练、评估、预测等内容。在 `ppcls/configs/ImageNet/SwinTransformerV2/` 中提供了 SwinTransformerV2 的训练配置，可以通过如下脚本启动训练：此部分内容可以参考[ResNet50 模型训练、评估和预测](./ResNet.md#3)。
 
 **备注：** 由于 SwinTransformer 系列模型默认使用的 GPU 数量为 8 个，所以在训练时，需要指定8个GPU，如`python3 -m paddle.distributed.launch --gpus="0,1,2,3,4,5,6,7" tools/train.py -c xxx.yaml`, 如果使用 4 个 GPU 训练，默认学习率需要减小一半，精度可能有损。
 

ppcls/arch/backbone/__init__.py

@@ -54,7 +54,7 @@ from .model_zoo.regnet import RegNetX_200MF, RegNetX_400MF, RegNetX_600MF, RegNe
 from .model_zoo.vision_transformer import ViT_small_patch16_224, ViT_base_patch16_224, ViT_base_patch16_384, ViT_base_patch32_384, ViT_large_patch16_224, ViT_large_patch16_384, ViT_large_patch32_384
 from .model_zoo.distilled_vision_transformer import DeiT_tiny_patch16_224, DeiT_small_patch16_224, DeiT_base_patch16_224, DeiT_tiny_distilled_patch16_224, DeiT_small_distilled_patch16_224, DeiT_base_distilled_patch16_224, DeiT_base_patch16_384, DeiT_base_distilled_patch16_384
 from .legendary_models.swin_transformer import SwinTransformer_tiny_patch4_window7_224, SwinTransformer_small_patch4_window7_224, SwinTransformer_base_patch4_window7_224, SwinTransformer_base_patch4_window12_384, SwinTransformer_large_patch4_window7_224, SwinTransformer_large_patch4_window12_384
-from .model_zoo.swin_transformerv2 import SwinTransformerV2_tiny_patch4_window8_256, SwinTransformerV2_small_patch4_window8_256, SwinTransformerV2_base_patch4_window8_256, SwinTransformerV2_tiny_patch4_window16_256, SwinTransformerV2_small_patch4_window16_256, SwinTransformerV2_base_patch4_window16_256, SwinTransformerV2_base_patch4_window12to16_256, SwinTransformerV2_base_patch4_window24_384, SwinTransformerV2_large_patch4_window16_256, SwinTransformerV2_large_patch4_window24_384
+from .model_zoo.swin_transformer_v2 import SwinTransformerV2_tiny_patch4_window8_256, SwinTransformerV2_small_patch4_window8_256, SwinTransformerV2_base_patch4_window8_256, SwinTransformerV2_tiny_patch4_window16_256, SwinTransformerV2_small_patch4_window16_256, SwinTransformerV2_base_patch4_window16_256, SwinTransformerV2_base_patch4_window24_384, SwinTransformerV2_large_patch4_window16_256, SwinTransformerV2_large_patch4_window24_384
 from .model_zoo.cswin_transformer import CSWinTransformer_tiny_224, CSWinTransformer_small_224, CSWinTransformer_base_224, CSWinTransformer_large_224, CSWinTransformer_base_384, CSWinTransformer_large_384
 from .model_zoo.mixnet import MixNet_S, MixNet_M, MixNet_L
 from .model_zoo.rexnet import ReXNet_1_0, ReXNet_1_3, ReXNet_1_5, ReXNet_2_0, ReXNet_3_0