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debug (#2934)

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* debug: fix model name

* fix

* fix Infer.transforms.ResizeImage
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Tingquan Gao 2023-09-19 16:08:09 +08:00 committed by GitHub
parent 2200f30052
commit fe12d63181
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4 changed files with 9 additions and 5 deletions
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2
docs/zh_CN/models/ImageNet1k/MixNet.md
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@ -38,7 +38,7 @@ MixNet 是谷歌出的一篇关于轻量级网络的文章，主要工作就在
### 1.2 模型指标 ### 1.2 模型指标
| Models | Top1 | Top5 | Reference<br>top1| Reference<br>top5 | FLOPs<br>(M) | Params<br/>(M) | | Models | Top1 | Top5 | Reference<br>top1| Reference<br>top5 | FLOPs<br>(M) | Params<br/>(M) |
|:--:|:--:|:--:|:--:|:--:|----| |:--:|:--:|:--:|:--:|:--:|:--:|:--:|
| MixNet_S | 76.28 | 92.99 | 75.8 | - | 252.977 | 4.167 | | MixNet_S | 76.28 | 92.99 | 75.8 | - | 252.977 | 4.167 |
| MixNet_M | 77.67 | 93.64 | 77.0 | - | 357.119 | 5.065 | | MixNet_M | 77.67 | 93.64 | 77.0 | - | 357.119 | 5.065 |
| MixNet_L | 78.60 | 94.37 | 78.9 | - | 579.017 | 7.384 | | MixNet_L | 78.60 | 94.37 | 78.9 | - | 579.017 | 7.384 |

4
ppcls/configs/CLIP/CLIP_vit_base_patch16_224_finetune.yaml
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@ -133,7 +133,9 @@ Infer:
to_rgb: True to_rgb: True
channel_first: False channel_first: False
- ResizeImage: - ResizeImage:
resize_short: 256 resize_short: 224
interpolation: bicubic
backend: pil
- CropImage: - CropImage:
size: 224 size: 224
- NormalizeImage: - NormalizeImage:

4
ppcls/configs/CLIP/CLIP_vit_large_patch16_224_finetune.yaml → ppcls/configs/CLIP/CLIP_vit_large_patch14_224_finetune.yaml
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@ -133,7 +133,9 @@ Infer:
to_rgb: True to_rgb: True
channel_first: False channel_first: False
- ResizeImage: - ResizeImage:
resize_short: 256 resize_short: 224
interpolation: bicubic
backend: pil
- CropImage: - CropImage:
size: 224 size: 224
- NormalizeImage: - NormalizeImage:

4
ppcls/loss/tripletangularmarginloss.py
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@ -59,7 +59,7 @@ class TripletAngularMarginLoss(nn.Layer):
""" """
Args: Args:
inputs: feature matrix with shape (batch_size, feat_dim) inputs: feature matrix with shape (batch_size, feat_dim)
target: ground truth labels with shape (num_classes) target: ground truth labels with shape (batch_size)
""" """
inputs = input[self.feature_from] inputs = input[self.feature_from]
@ -160,7 +160,7 @@ class TripletAngularMarginLoss_XBM(TripletAngularMarginLoss):
""" """
Args: Args:
inputs: feature matrix with shape (batch_size, feat_dim) inputs: feature matrix with shape (batch_size, feat_dim)
target: ground truth labels with shape (num_classes) target: ground truth labels with shape (batch_size)
""" """
feats = input[self.feature_from] feats = input[self.feature_from]
if self.normalize_feature: if self.normalize_feature: