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!