Merge branch 'main' into vision-perturbation

Author: someshsingh22

code_soup/common/vision/models/__init__.py

@@ -1,2 +1,38 @@
-from code_soup.common.vision.models.allconvnet import AllConvNet
+from torchvision.models import (
+    alexnet,
+    densenet121,
+    densenet161,
+    densenet169,
+    densenet201,
+    googlenet,
+    inception_v3,
+    mnasnet0_5,
+    mnasnet0_75,
+    mnasnet1_0,
+    mnasnet1_3,
+    mobilenet_v2,
+    mobilenet_v3_large,
+    mobilenet_v3_small,
+    resnet18,
+    resnet34,
+    resnet50,
+    resnet101,
+    resnet152,
+    resnext50_32x4d,
+    resnext101_32x8d,
+    shufflenet_v2_x0_5,
+    shufflenet_v2_x1_0,
+    shufflenet_v2_x1_5,
+    shufflenet_v2_x2_0,
+    squeezenet1_0,
+    squeezenet1_1,
+    vgg11,
+    vgg13,
+    vgg16,
+    vgg19,
+    wide_resnet50_2,
+    wide_resnet101_2,
+)
+
+from code_soup.common.vision.models.allconvnet import AllConvNet
 from code_soup.common.vision.models.nin import NIN

code_soup/common/vision/models/readme.md

@@ -4,3 +4,14 @@ List of implemented models
 ---
 1. [AllConvNet](allconvnet.py), [Striving for Simplicity: The All Convolutional Net](https://arxiv.org/abs/1412.6806)
 2. [Network in Network](nin.py), [Network In Network](https://arxiv.org/abs/1312.4400)
+
+# Notes on existing Torchvision models
+
+| Model  | Input sizes |
+| ------------- | ------------- |
+| AlexNet  |  Pre-trained to work on RGB images of sizes 256 x 256. Input to the first layer is a random crop of size 227 x 227 (not 224 x 224 as mentioned in the paper). The required minimum input size of the model is 227x227.|
+| VGG-net  | Pre-trained to work on RGB images of sizes 256 x 256, cropped to 224 x 224. IThe required minimum input size of the model is 224x224. |
+| ResNet | Pre-trained to work on RGB images of sizes 256 x 256, cropped to 224 x 244. IThe required minimum input size of the model is 224x224. |
+| Inception-v3 | Pre-trained to work on RGB images of sizes 299 x 299. The pre-trained model, with default aux_logits=True, would work for images of size>=299x299 (example: ImageNet), but not for images of size<299x299 (example: CIFAR-10 and MNIST).|
+
+All other pre-trained models require a minimum input size of 224 x 224.

tests/test_common/test_vision/test_models/__init__.py

@@ -1 +1,2 @@
-from tests.test_common.test_vision.test_models.test_allconv import TestAllConvNet
+from tests.test_common.test_vision.test_models.test_allconv import TestAllConvNet
+from tests.test_common.test_vision.test_models.test_nin import TestNIN