Pytorch I3D Resnet model on a custom dataset

This is a follow-up to a couple of questions I asked before...I want to fine-tune the I3D model for action recognition from Pytorch hub (which is pre-trained on Kinetics 400 classes) on a custom dataset, where I have 4 possible output classes.

I'm loading the model and modifying the last layer by:

model = torch.hub.load("facebookresearch/pytorchvideo", "i3d_r50", pretrained=True)num_classes = 4model.blocks[6].proj = torch.nn.Linear(2048, num_classes)

I defined the getitem method of my Dataset to return:

def __getitem__(self, ind):    [...]    return processed_images, target

where processed_images and target are Tensors, with shapes:

>>processed_images.shapetorch.Size([5, 224, 224, 3])>>target.shapetorch.Size([4])

Basically, processed_images is a sequence of 5 RGB images, each with shape (224, 224), while target is the one-hot encoding for the target classes.

In the training part, I have:

model.train()model.to(device)train_dataloader = torch.utils.data.DataLoader(        train_dataset,        batch_size=batch_size,        shuffle=True,        drop_last=False,        persistent_workers=False,        timeout=0,    )for epoch in range(number_of_epochs):    for batch_ind, batch_data in enumerate(train_dataloader):        # Extract data and label        datas, labels = batch_data        # move to device        datas_ = datas.to(device)        labels_ = labels.to(device)        weights_ = weights.to(device)        # permute axes (changing from [22, 5, 224, 224, 3] -> [22, 3, 5, 224, 224, 3]          datas_ = datas_.permute(0, 4, 1, 2, 3)        preds_ = model(datas_)

But I'm getting an error in the forward method of ResNetBasicHead:

Exception has occurred: RuntimeErrorinput image (T: 2 H: 14 W: 14) smaller than kernel size (kT: 4 kH: 7 kW: 7)  File "/home/c.demasi/.cache/torch/hub/facebookresearch_pytorchvideo_main/pytorchvideo/models/head.py", line 374, in forward    x = self.pool(x)  File "/home/c.demasi/.cache/torch/hub/facebookresearch_pytorchvideo_main/pytorchvideo/models/net.py", line 43, in forward    x = block(x)  File "/home/c.demasi/work/projects/ball_shot_action_detection_dev_environment/src/train_torch.py", line 271, in train    preds_ = model(datas_)  File "/home/c.demasi/work/projects/ball_shot_action_detection_dev_environment/src/train_torch.py", line 571, in train_roi    train(training_parameters, train_from_existing_path=None, perform_tests=perform_tests, config=config)  File "/home/c.demasi/work/projects/ball_shot_action_detection_dev_environment/train.py", line 13, in <module>    train_roi(config=config, perform_tests=False)RuntimeError: input image (T: 2 H: 14 W: 14) smaller than kernel size (kT: 4 kH: 7 kW: 7)

Any idea how to solve this?