create_dataloaders

from torch.utils.data import TensorDataset, DataLoader

batch_size = 64

train_features = torch.Tensor(X_train_arr)
train_targets = torch.Tensor(y_train_arr)
val_features = torch.Tensor(X_val_arr)
val_targets = torch.Tensor(y_val_arr)
test_features = torch.Tensor(X_test_arr)
test_targets = torch.Tensor(y_test_arr)

train = TensorDataset(train_features, train_targets)
val = TensorDataset(val_features, val_targets)
test = TensorDataset(test_features, test_targets)

train_loader = DataLoader(train, batch_size=batch_size, shuffle=False, drop_last=True)
val_loader = DataLoader(val, batch_size=batch_size, shuffle=False, drop_last=True)
test_loader = DataLoader(test, batch_size=batch_size, shuffle=False, drop_last=True)
test_loader_one = DataLoader(test, batch_size=1, shuffle=False, drop_last=True)