polish download pretrain

2526d5cb · WuHaobo · e3ca763d · 2526d5cb · 2526d5cb · 2526d5cb
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Showing with 121 addition and 119 deletion

configs/pretrained.list configs/pretrained.list +117 -117

ppcls/utils/check.py ppcls/utils/check.py +1 -0

ppcls/utils/model_zoo.py ppcls/utils/model_zoo.py +3 -2

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--- a/configs/pretrained.list
+++ b/configs/pretrained.list
- ResNet18
+ResNet18
- ResNet34
+ResNet34
- ResNet50
+ResNet50
- ResNet101
+ResNet101
- ResNet152
+ResNet152
- ResNet50_vc
+ResNet50_vc
- ResNet18_vd
+ResNet18_vd
- ResNet34_vd
+ResNet34_vd
- ResNet50_vd
+ResNet50_vd
- ResNet50_vd_v2
+ResNet50_vd_v2
- ResNet101_vd
+ResNet101_vd
- ResNet152_vd
+ResNet152_vd
- ResNet200_vd
+ResNet200_vd
- ResNet50_vd_ssld
+ResNet50_vd_ssld
- MobileNetV3_large_x0_35
+MobileNetV3_large_x0_35
- MobileNetV3_large_x0_5
+MobileNetV3_large_x0_5
- MobileNetV3_large_x0_75
+MobileNetV3_large_x0_75
- MobileNetV3_large_x1_0
+MobileNetV3_large_x1_0
- MobileNetV3_large_x1_25
+MobileNetV3_large_x1_25
- MobileNetV3_small_x0_35
+MobileNetV3_small_x0_35
- MobileNetV3_small_x0_5
+MobileNetV3_small_x0_5
- MobileNetV3_small_x0_75
+MobileNetV3_small_x0_75
- MobileNetV3_small_x1_0
+MobileNetV3_small_x1_0
- MobileNetV3_small_x1_25
+MobileNetV3_small_x1_25
- MobileNetV3_large_x1_0_ssld
+MobileNetV3_large_x1_0_ssld
- MobileNetV3_large_x1_0_ssld_int8
+MobileNetV3_large_x1_0_ssld_int8
- MobileNetV3_small_x1_0_ssld
+MobileNetV3_small_x1_0_ssld
- MobileNetV2_x0_25
+MobileNetV2_x0_25
- MobileNetV2_x0_5
+MobileNetV2_x0_5
- MobileNetV2_x0_75
+MobileNetV2_x0_75
- MobileNetV2
+MobileNetV2
- MobileNetV2_x1_5
+MobileNetV2_x1_5
- MobileNetV2_x2_0
+MobileNetV2_x2_0
- MobileNetV2_ssld
+MobileNetV2_ssld
- MobileNetV1_x0_25
+MobileNetV1_x0_25
- MobileNetV1_x0_5
+MobileNetV1_x0_5
- MobileNetV1_x0_75
+MobileNetV1_x0_75
- MobileNetV1
+MobileNetV1
- MobileNetV1_ssld
+MobileNetV1_ssld
- ShuffleNetV2_x0_25
+ShuffleNetV2_x0_25
- ShuffleNetV2_x0_33
+ShuffleNetV2_x0_33
- ShuffleNetV2_x0_5
+ShuffleNetV2_x0_5
- ShuffleNetV2
+ShuffleNetV2
- ShuffleNetV2_x1_5
+ShuffleNetV2_x1_5
- ShuffleNetV2_x2_0
+ShuffleNetV2_x2_0
- ShuffleNetV2_swish
+ShuffleNetV2_swish
- ResNeXt50_32x4d
+ResNeXt50_32x4d
- ResNeXt50_64x4d
+ResNeXt50_64x4d
- ResNeXt101_32x4d
+ResNeXt101_32x4d
- ResNeXt101_64x4d
+ResNeXt101_64x4d
- ResNeXt152_32x4d
+ResNeXt152_32x4d
- ResNeXt152_64x4d
+ResNeXt152_64x4d
- ResNeXt50_vd_32x4d
+ResNeXt50_vd_32x4d
- ResNeXt50_vd_64x4d
+ResNeXt50_vd_64x4d
- ResNeXt101_vd_32x4d
+ResNeXt101_vd_32x4d
- ResNeXt101_vd_64x4d
+ResNeXt101_vd_64x4d
- ResNeXt152_vd_32x4d
+ResNeXt152_vd_32x4d
- ResNeXt152_vd_64x4d
+ResNeXt152_vd_64x4d
- SE_ResNet18_vd
+SE_ResNet18_vd
- SE_ResNet34_vd
+SE_ResNet34_vd
- SE_ResNet50_vd
+SE_ResNet50_vd
- SE_ResNeXt50_32x4d
+SE_ResNeXt50_32x4d
- SE_ResNeXt101_32x4d
+SE_ResNeXt101_32x4d
- SE_ResNeXt50_vd_32x4d
+SE_ResNeXt50_vd_32x4d
- SENet154_vd
+SENet154_vd
- Res2Net50_26w_4s
+Res2Net50_26w_4s
- Res2Net50_vd_26w_4s
+Res2Net50_vd_26w_4s
- Res2Net50_14w_8s
+Res2Net50_14w_8s
- Res2Net101_vd_26w_4s
+Res2Net101_vd_26w_4s
- Res2Net200_vd_26w_4s
+Res2Net200_vd_26w_4s
- GoogLeNet
+GoogLeNet
- InceptionV4
+InceptionV4
- Xception41
+Xception41
- Xception41_deeplab
+Xception41_deeplab
- Xception65
+Xception65
- Xception65_deeplab
+Xception65_deeplab
- Xception71
+Xception71
- HRNet_W18_C
+HRNet_W18_C
- HRNet_W30_C
+HRNet_W30_C
- HRNet_W32_C
+HRNet_W32_C
- HRNet_W40_C
+HRNet_W40_C
- HRNet_W44_C
+HRNet_W44_C
- HRNet_W48_C
+HRNet_W48_C
- HRNet_W64_C
+HRNet_W64_C
- DPN68
+DPN68
- DPN92
+DPN92
- DPN98
+DPN98
- DPN107
+DPN107
- DPN131
+DPN131
- DenseNet121
+DenseNet121
- DenseNet161
+DenseNet161
- DenseNet169
+DenseNet169
- DenseNet201
+DenseNet201
- DenseNet264
+DenseNet264
- EfficientNetB0_small
+EfficientNetB0_small
- EfficientNetB0
+EfficientNetB0
- EfficientNetB1
+EfficientNetB1
- EfficientNetB2
+EfficientNetB2
- EfficientNetB3
+EfficientNetB3
- EfficientNetB4
+EfficientNetB4
- EfficientNetB5
+EfficientNetB5
- EfficientNetB6
+EfficientNetB6
- EfficientNetB7
+EfficientNetB7
- ResNeXt101_32x8d_wsl
+ResNeXt101_32x8d_wsl
- ResNeXt101_32x16d_wsl
+ResNeXt101_32x16d_wsl
- ResNeXt101_32x32d_wsl
+ResNeXt101_32x32d_wsl
- ResNeXt101_32x48d_wsl
+ResNeXt101_32x48d_wsl
- Fix_ResNeXt101_32x48d_wsl
+Fix_ResNeXt101_32x48d_wsl
- AlexNet
+AlexNet
- SqueezeNet1_0
+SqueezeNet1_0
- SqueezeNet1_1
+SqueezeNet1_1
- VGG11
+VGG11
- VGG13
+VGG13
- VGG16
+VGG16
- VGG19
+VGG19
- DarkNet53
+DarkNet53
- ResNet50_ACNet_deploy
+ResNet50_ACNet_deploy
--- a/ppcls/utils/check.py
+++ b/ppcls/utils/check.py
@@ -20,6 +20,7 @@ import sys
 import paddle.fluid as fluid
+from ppcls.modeling import get_architectures
 from ppcls.modeling import similar_architectures
 from ppcls.utils import logger

--- a/ppcls/utils/model_zoo.py
+++ b/ppcls/utils/model_zoo.py
@@ -25,7 +25,6 @@ import zipfile
 from ppcls.modeling import similar_architectures
 from ppcls.utils.check import check_architecture
-from ppcls.utils.config import get_config
 from ppcls.utils import logger
 __all__ = ['get']
@@ -172,7 +171,9 @@ def _decompress(fname):
 def _check_pretrained_name(architecture):
    assert isinstance(architecture, str), \
            ("the type of architecture({}) should be str". format(architecture))
-    similar_names = similar_architectures(architecture, get_config('../../../configs/pretrained.list'))
+    with open('./configs/pretrained.list') as flist:
+        pretrained = [line.strip() for line in flist]
+    similar_names = similar_architectures(architecture, pretrained)
    model_list = ', '.join(similar_names)
    err = "{} is not exist! Maybe you want: [{}]" \
          "".format(architecture, model_list)