chore: flake8 + typos in notebooks + readme & index

deel-ai · Apr 18, 2024 · 8678b60 · 8678b60
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diff --git a/README.md b/README.md
@@ -177,6 +177,8 @@ Currently, **oodeel** includes the following baselines:
 | NMD | [Neural Mean Discrepancy for Efficient Out-of-Distribution Detection](https://openaccess.thecvf.com/content/CVPR2022/html/Dong_Neural_Mean_Discrepancy_for_Efficient_Out-of-Distribution_Detection_CVPR_2022_paper.html) | CVPR 2022 | planned |
 | Gram | [Detecting Out-of-Distribution Examples with Gram Matrices](https://proceedings.mlr.press/v119/sastry20a.html) | ICML 2020 | avail [tensorflow](docs/notebooks/tensorflow/demo_gram_tf.ipynb) or  [torch](docs/notebooks/torch/demo_gram_torch.ipynb) |
 | GEN | [GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection](https://openaccess.thecvf.com/content/CVPR2023/html/Liu_GEN_Pushing_the_Limits_of_Softmax-Based_Out-of-Distribution_Detection_CVPR_2023_paper.html) | CVPR 2023 | avail [tensorflow](docs/notebooks/tensorflow/demo_gen_tf.ipynb) or [torch](docs/notebooks/torch/demo_gen_torch.ipynb) |
+| ASH | [Extremely Simple Activation Shaping for Out-of-Distribution Detection](http://arxiv.org/abs/2310.00227) | ICLR 2023 | avail [tensorflow](docs/notebooks/tensorflow/demo_ash_tf.ipynb) or [torch](docs/notebooks/torch/demo_ash_torch.ipynb) |
+| SCALE | [Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement](https://arxiv.org/abs/2111.12797) | ICLR 2024 | avail [tensorflow](docs/notebooks/tensorflow/demo_scale_tf.ipynb) or [torch](docs/notebooks/torch/demo_scale_torch.ipynb) |
 
 
 

diff --git a/docs/index.md b/docs/index.md
@@ -176,6 +176,8 @@ Currently, **oodeel** includes the following baselines:
 | NMD | [Neural Mean Discrepancy for Efficient Out-of-Distribution Detection](https://openaccess.thecvf.com/content/CVPR2022/html/Dong_Neural_Mean_Discrepancy_for_Efficient_Out-of-Distribution_Detection_CVPR_2022_paper.html) | CVPR 2022 | planned |
 | Gram | [Detecting Out-of-Distribution Examples with Gram Matrices](https://proceedings.mlr.press/v119/sastry20a.html) | ICML 2020 | avail [tensorflow](./notebooks/tensorflow/demo_gram_tf.ipynb) or  [torch](./notebooks/torch/demo_gram_torch.ipynb) |
 | GEN | [GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection](https://openaccess.thecvf.com/content/CVPR2023/html/Liu_GEN_Pushing_the_Limits_of_Softmax-Based_Out-of-Distribution_Detection_CVPR_2023_paper.html) | CVPR 2023 | avail [tensorflow](./notebooks/tensorflow/demo_gen_tf.ipynb) or [torch](./notebooks/torch/demo_gen_torch.ipynb) |
+| ASH | [Extremely Simple Activation Shaping for Out-of-Distribution Detection](http://arxiv.org/abs/2310.00227) | ICLR 2023 | avail [tensorflow](docs/notebooks/tensorflow/demo_ash_tf.ipynb) or [torch](docs/notebooks/torch/demo_ash_torch.ipynb) |
+| SCALE | [Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement](https://arxiv.org/abs/2111.12797) | ICLR 2024 | avail [tensorflow](docs/notebooks/tensorflow/demo_scale_tf.ipynb) or [torch](docs/notebooks/torch/demo_scale_torch.ipynb) |
 
 
 **Oodeel** also includes standard training functions with data augmentation and learning rate scheduler for toy convnet models or models from `keras.applications` in [tf_training_tools.py](https://github.com/deel-ai/oodeel/tree/master/oodeel/utils/tf_training_tools.py) and `torchvision.models` in [torch_training_tools.py](https://github.com/deel-ai/oodeel/tree/master/oodeel/utils/torch_training_tools.py) files. These functions come in handy for benchmarks like *leave-k-classes-out* that requires retraining models on a subset of dataset classes.

diff --git a/docs/notebooks/tensorflow/demo_scale_tf.ipynb b/docs/notebooks/tensorflow/demo_scale_tf.ipynb
@@ -18,7 +18,7 @@
                 "\n",
                 "**Reference**  \n",
                 "_Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement_, ICLR 2024\n",
-                "<https://arxiv.org/pdf/2111.12797.pdf>"
+                "<http://arxiv.org/abs/2310.00227>"
             ]
         },
         {

diff --git a/docs/notebooks/torch/demo_scale_torch.ipynb b/docs/notebooks/torch/demo_scale_torch.ipynb
@@ -18,7 +18,7 @@
                 "\n",
                 "**Reference**  \n",
                 "_Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement_, ICLR 2024\n",
-                "<https://arxiv.org/pdf/2111.12797.pdf>\n"
+                "<http://arxiv.org/abs/2310.00227>\n"
             ]
         },
         {

diff --git a/oodeel/extractor/torch_feature_extractor.py b/oodeel/extractor/torch_feature_extractor.py
@@ -24,7 +24,6 @@
 from typing import get_args
 from typing import Optional
 
-import numpy as np
 import torch
 from torch import nn
 from torch.utils.data import DataLoader