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"""
Example: Creating a Custom Dataset
This example shows how to add a new dataset following the project architecture.
"""
from torch.utils.data import Dataset
from typing import Dict
import torch
from src.data_module.dataset import register_dataset
@register_dataset("time_series")
class TimeSeriesDataset(Dataset):
"""
Time series dataset for sequence modeling.
Args:
sequences: List of time series sequences
seq_length: Fixed sequence length (pad or truncate if needed)
"""
def __init__(self, sequences: list, seq_length: int = 100):
self.sequences = sequences
self.seq_length = seq_length
def __len__(self) -> int:
return len(self.sequences)
def __getitem__(self, i: int) -> Dict[str, torch.Tensor]:
sequence = self.sequences[i]
# Pad or truncate to fixed length
if len(sequence) < self.seq_length:
padding = torch.zeros(self.seq_length - len(sequence))
sequence = torch.cat([sequence, padding])
else:
sequence = sequence[:self.seq_length]
return {
"input": sequence,
"label": sequence, # For autoencoder, etc.
"length": torch.tensor(min(len(self.sequences[i]), self.seq_length))
}
# Usage in training:
# from src.data_module.dataset import DatasetFactory
# dataset = DatasetFactory("time_series")(sequences=training_data, seq_length=128)
# dataloader = DataLoader(dataset, batch_size=32, shuffle=True)
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