!pip install jovian --upgrade --quiet

import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import torch
import torchvision
import tarfile
from PIL import Image
import torchvision.models as models
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm
import torchvision.transforms as T
from sklearn.metrics import f1_score
import torch.nn.functional as F
import torch.nn as nn
from torchvision.utils import make_grid
%matplotlib inline
from torchvision.datasets.utils import download_url
from torch.utils.data import Dataset, random_split, DataLoader
from torchvision.datasets import ImageFolder
from torchvision.transforms import ToTensor

import os
import torch
import torchvision
import tarfile
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
import torchvision.transforms as tt
from torch.utils.data import random_split
from torchvision.utils import make_grid
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

matplotlib.rcParams['figure.facecolor'] = '#ffffff'

project_name = '04-assignment-ramysaleem-seismic-data'

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