whats the easiest way to test this code app

[pythonyalfa]

I cloned this app into pycharm and copied the initial file when i ran "python file.py" it began downloading 5 gigs of data. Did I do something wrong or is this what its supposed to do ? Thanks for helping out ?

import data import torch from models import imagebind_model from models.imagebind_model import ModalityType

text_list=["A dog.", "A car", "A bird"] image_paths=[".assets/dog_image.jpg", ".assets/car_image.jpg", ".assets/bird_image.jpg"] audio_paths=[".assets/dog_audio.wav", ".assets/car_audio.wav", ".assets/bird_audio.wav"]

device = "cuda:0" if torch.cuda.is_available() else "cpu"

Instantiate model

model = imagebind_model.imagebind_huge(pretrained=True) model.eval() model.to(device)

Load data

inputs = { ModalityType.TEXT: data.load_and_transform_text(text_list, device), ModalityType.VISION: data.load_and_transform_vision_data(image_paths, device), ModalityType.AUDIO: data.load_and_transform_audio_data(audio_paths, device), }

with torch.no_grad(): embeddings = model(inputs)

print( "Vision x Text: ", torch.softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.TEXT].T, dim=-1), ) print( "Audio x Text: ", torch.softmax(embeddings[ModalityType.AUDIO] @ embeddings[ModalityType.TEXT].T, dim=-1), ) print( "Vision x Audio: ", torch.softmax(embeddings[ModalityType.VISION] @ embeddings[ModalityType.AUDIO].T, dim=-1), )

Expected output:

#

Vision x Text:

tensor([[9.9761e-01, 2.3694e-03, 1.8612e-05],

[3.3836e-05, 9.9994e-01, 2.4118e-05],

[4.7997e-05, 1.3496e-02, 9.8646e-01]])

#

Audio x Text:

tensor([[1., 0., 0.],

[0., 1., 0.],

[0., 0., 1.]])

#

Vision x Audio:

tensor([[0.8070, 0.1088, 0.0842],

[0.1036, 0.7884, 0.1079],

[0.0018, 0.0022, 0.9960]])

[kilowrk]

I Believe that is the model being downloaded, I'm pretty sure this is normal behaviour.