Add info in readme and fix name mistake

README.md

@@ -154,7 +154,6 @@ The distance measure in parentheses.
 |     **EOTPGD**<br />(Linf)      | Comment on "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network" ([Zimmermann, 2019](https://arxiv.org/abs/1907.00895))          | [EOT](https://arxiv.org/abs/1707.07397)+PGD                                                                            |
 |    **APGD**<br />(Linf, L2)     | Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks ([Croce et al., 2020](https://arxiv.org/abs/2001.03994)) |                                                                                                                        |
 |    **APGDT**<br />(Linf, L2)    | Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks ([Croce et al., 2020](https://arxiv.org/abs/2001.03994)) | Targeted APGD                                                                                                          |
-|   **FAB**<br />(Linf, L2, L1)   | Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack ([Croce et al., 2019](https://arxiv.org/abs/1907.02044))                    |                                                                                                                        |
 |   **Square**<br />(Linf, L2)    | Square Attack: a query-efficient black-box adversarial attack via random search ([Andriushchenko et al., 2019](https://arxiv.org/abs/1912.00049))         |                                                                                                                        |
 | **AutoAttack**<br />(Linf, L2)  | Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks ([Croce et al., 2020](https://arxiv.org/abs/2001.03994)) | APGD+APGDT+FAB+Square                                                                                                  |
 |     **DeepFool**<br />(L2)      | DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks ([Moosavi-Dezfooli et al., 2016](https://arxiv.org/abs/1511.04599))                   |                                                                                                                        |
@@ -181,6 +180,9 @@ The distance measure in parentheses.
 | **CWBSL2 (Binary Search Version)**<br />(L2) | Towards Evaluating the Robustness of Neural Networks ([Carlini N, Wagner D, 2017](https://arxiv.org/abs/1608.046443))                 | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                               |
 | **CWBSLinf (Binary Search Version)**<br />(Linf) | Towards Evaluating the Robustness of Neural Networks ([Carlini N, Wagner D, 2017](https://arxiv.org/abs/1608.046443))                 | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                               |
 | **ESPGD (Early-Stopped PGD Version)**<br />(Linf) | Attacks Which Do Not Kill Training Make Adversarial Learning Stronger ([Zhang, Jingfeng, 2020](https://arxiv.org/abs/2002.11242))                 | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                               |
+|   **FAB**<br />(Linf)   | Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack ([Croce et al., 2019](https://arxiv.org/abs/1907.02044))                    | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                       |
+|   **FABL1**<br />(L1)   | Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack ([Croce et al., 2019](https://arxiv.org/abs/1907.02044))                    | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                       |
+|   **FABL2**<br />(L2)   | Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack ([Croce et al., 2019](https://arxiv.org/abs/1907.02044))                    | :heart_eyes: Contributor [Riko Naka](https://github.com/rikonaka)                       |
 
 ## :bar_chart: Performance Comparison
 

torchattacks/attacks/fabl2.py

@@ -34,7 +34,7 @@ class FABL2(Attack):
     """
 
     def __init__(self, model, eps=8/255, n_restarts=1, n_iter=10, alpha_max=0.1, eta=1.05, beta=0.9, las=False):
-        super().__init__("FABL1", model)
+        super().__init__("FABL2", model)
         self.eps = eps
         self.n_restarts = n_restarts
         self.n_iter = n_iter