Hi everyone!
I have this Dataset class:
“”"
class Dataset(Dataset):
# Constructor
def __init__(self, train = True):
    
    data = pd.read_csv('https://s3.us.cloud-object-storage.appdomain.cloud/cf-courses-data/CognitiveClass/DL0110EN/ML03210EN_Final_Assignment/LoLMatchData.csv')
    
    if (train):
        self.x = torch.tensor(data.iloc[0:7903, :].drop(['blueWins'], axis=1).values, dtype=torch.float)
        # standardizing the data
        self.x = (self.x - self.x.mean(dim=0))/self.x.std(dim=0)
        self.y = torch.tensor(data.loc[0:7903, 'blueWins'].values, dtype=torch.float).reshape((7904,1))
        self.len = self.x.shape[0]
    else:
        self.x = torch.tensor(data.iloc[7904:, :].drop(['blueWins'], axis=1).values, dtype=torch.float)
        # standardizing the data
        self.x = (self.x - self.x.mean(dim=0))/self.x.std(dim=0)
        self.y = torch.tensor(data.loc[7904:, 'blueWins'].values, dtype=torch.float).reshape((1975,1))
        self.len = self.x.shape[0]
        

# Get the length
def __len__(self):
    return self.len

# Getter
def __getitem__(self, idx):
    
    x = self.x[idx]
    
    y = self.y[idx]

    return x, y

“”"
I need to use this Dataset class to create a dataset object for training and testing. Not to mention set the training parameter to the correct value.
I would be pleased if anyone could help me with this task.
Thank you in Advance!