Comparing Models for Different Tasks (Image Classification v.s. Object Detection)?

[bryanbocao]

Thanks for sharing the code. I see that the models in the examples in this repo are all for classification. I was wondering if we can compare two models that do different tasks such as one for classification (Reset) and the other for object detection (YOLO)?

Thanks!

[bryanbocao]

Tried

import os
import torch
from torchvision.models import resnet18 # edit
from torchvision.models.detection import fasterrcnn_resnet50_fpn # edit
# from torchvision.models.detection.SSD import ssd300_vgg16 # edit
from torchvision.datasets import CIFAR10 # edit
# import torchvision.datasets as dataset
# print('\n dir(dataset): ', dir(dataset))
# from torchvision.datasets import CocoDetection # edit
from torch.utils.data import DataLoader
import torchvision.transforms as transforms
import numpy as np
import random
from torch_cka import CKA

# print('\n dir(CocoDetection): ', dir(CocoDetection))

if not os.path.exists('../exps'): os.makedirs('../exps')

def seed_worker(worker_id):
    worker_seed = torch.initial_seed() % 2**32
    np.random.seed(worker_seed)
    random.seed(worker_seed)

g = torch.Generator()
g.manual_seed(0)
np.random.seed(0)
random.seed(0)

model1_name, model2_name = 'resnet18', 'F-RCNN' # edit
model1 = resnet18(pretrained=True) # edit
model2 = fasterrcnn_resnet50_fpn(pretrained=True) # edit

transform = transforms.Compose(
    [transforms.ToTensor(),
     transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225))])

batch_size = 16 # 64 # 256

dataset = CIFAR10(root='../data/',
                  train=False,
                  download=True,
                  transform=transform)

dataloader = DataLoader(dataset,
                        batch_size=batch_size,
                        shuffle=False,
                        worker_init_fn=seed_worker,
                        generator=g,)

cka = CKA(model1, model2,
        model1_name=model1_name, model2_name=model2_name,
        device='cuda')

cka.compare(dataloader)
cka.plot_results(save_path="../exps/{}_{}.jpg".format(model1_name, model2_name))

but got

python3 resnet18_FRCNN.py
/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=FasterRCNN_ResNet50_FPN_Weights.COCO_V1`. You can also use `weights=FasterRCNN_ResNet50_FPN_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
Files already downloaded and verified
/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torch_cka/cka.py:69: UserWarning: Model 2 seems to have a lot of layers. Consider giving a list of layers whose features you are concerned with through the 'model2_layers' parameter. Your CPU/GPU will thank you :)
  warn("Model 2 seems to have a lot of layers. " \
/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torch_cka/cka.py:145: UserWarning: Dataloader for Model 2 is not given. Using the same dataloader for both models.
  warn("Dataloader for Model 2 is not given. Using the same dataloader for both models.")
| Comparing features |:   0%|                                             | 0/625 [00:10<?, ?it/s]
Traceback (most recent call last):
  File "resnet18_FRCNN.py", line 55, in <module>
    cka.compare(dataloader)
  File "/home/brcao/Apps/anaconda3/envs/effi/lib/python3.8/site-packages/torch_cka/cka.py", line 172, in compare
    Y = feat2.flatten(1)
AttributeError: 'tuple' object has no attribute 'flatten'

Any help would be appreciated @AntixK. Thanks!

[ratom]

@bryanbocao . Have you solved the error AttributeError: 'tuple' object has no attribute 'flatten'. I got this error when I tried to compare ResNet and ViT. Is there any solution, please let me know

[bryanbocao]

@ratom unfortunately, not yet. I tried other projects later.

[bryanbocao]

@ratom The layer where I got the error seemed to be right after a backbone (haven't rigorously verified it). So I simply just find those layers with errors and ignore them.