Comparision between ResNet50 and ViT gives error

[ratom]

!pip install transformers
import torch
from torchvision import transforms
from torch.utils.data import Dataset, DataLoader
import torch.nn as nn
import torch.nn.functional as F
from transformers import ViTFeatureExtractor, ViTModel, ViTConfig, AutoConfig

Modify the model - ResNet

model_Res = torch.hub.load('pytorch/vision:v0.10.0', 'resnet50', pretrained=True)

Remove the last layer of the model Res

layers_Res = list(model_Res.children())
model_Res = nn.Sequential(*layers_Res[:-1])

Set the top layers to be not trainable

count = 0
for child in model_Res.children():
count += 1
if count < 8:
for param in child.parameters():
param.requires_grad = False

Modify the model - ViT model

model_trans = ViTModel.from_pretrained('google/vit-base-patch16-224-in21k')
count = 0
for child in model_trans.children():
count += 1
if count >= 4:
for param in child.parameters():
param.requires_grad = False

layers_trans = list(model_trans.children())
model_trans_top = nn.Sequential(*layers_trans[:-2])

model1 = model_Res
model2 = model_trans_top

cka = CKA(model1, model2,
model1_name="ResNet50", model2_name="ViT",
device='cuda')

cka.compare(dataloader)

cka.plot_results(save_path="/content/drive/MyDrive/resnet-ViTcompare.png")

i got this error ValueError: Input image size (3232) doesn't match model (224224).