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Add DataLoader implementation - #7
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Pull request overview
This PR introduces the initial PyTorch dataset + dataloader building blocks under services/ml/data/, intended to support the ML training data pipeline (loading paired clean/ and degraded/ .npy samples for training).
Changes:
- Added
BlackHoleDatasetfor loading pairedclean/degraded.npysamples as tensors. - Added
create_dataloaderhelper to construct a PyTorchDataLoaderfor the dataset.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.
| File | Description |
|---|---|
| services/ml/data/dataset.py | Adds a PyTorch Dataset for paired clean/degraded .npy training samples. |
| services/ml/data/dataloader.py | Adds a create_dataloader helper to build a PyTorch DataLoader over the dataset. |
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| import numpy as np | ||
| import torch | ||
| from torch.utils.data import Dataset | ||
| from pathlib import Path | ||
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| from torch.utils.data import DataLoader | ||
| from .dataset import BlackHoleDataset | ||
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| def create_dataloader(root_dir, batch_size=16): |
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