fix(dataset): distinguish offline fallback from corrupted CIFAR archives and batches

[rishiiicreates]

addresses #99

isolates the synthetic dataset fallback in CIFARDataset._load() strictly to network download failures and enforces fail-closed validation for local data corruption:

• narrowed exception handling during archive retrieval strictly to expected network/connectivity errors (urllib.error.URLError, TimeoutError, ConnectionError, http.client.HTTPException, OSError)
• if a download failure occurs, any partial archive artifact is unlinked before falling back to the fixed synthetic dataset
• archive extraction and batch parsing are moved outside the network try/except:
  • corrupted or truncated tar.gz archives raise directly
  • unsafe member paths with directory traversal raise ValueError
  • missing batch files raise FileNotFoundError
  • corrupted or truncated batch pickles raise pickle.UnpicklingError / EOFError
  • invalid batch structures missing b"data" or b"labels" raise ValueError
• added tests/test_dataset.py with 9 regression tests covering offline network fallback, corrupted archives, path traversal attempts, corrupted pickle files, malformed payload validation, and generator isolation (verifying global torch RNG state is untouched)

tested locally with pytest tests/test_dataset.py (9/9 passed in 0.52s) and full determinism suite pytest tests/test_experiment.py tests/test_dataset.py (32 passed, 3 cuda skipped).

Summary by CodeRabbit

• Bug Fixes
  • Dataset loading now uses sample data for network failures while allowing archive, extraction, and data-format errors to surface.
  • Invalid or incomplete CIFAR data is detected, and partial downloads are cleaned up when possible.
• New Features
  • CIFAR datasets can be loaded from a custom data directory.

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📥 Commits

Reviewing files that changed from the base of the PR and between 5dc237e and ae3a33e.

📒 Files selected for processing (3)

• pyproject.toml
• src/dataset.py
• tests/test_dataset.py

📝 Walkthrough

Walkthrough

The dataset loaders now distinguish network failures from archive, extraction, and parsing errors. CIFAR loading accepts an optional data directory, validates batch data, and uses fixed synthetic data when a download fails due to a network error.

Changes

Dataset loading behavior

Layer / File(s)	Summary
Network-error fallback behavior src/dataset.py	A shared error tuple identifies network failures. The Shakespeare loader now falls back only for those errors; other exceptions propagate.
CIFAR configuration and loading src/dataset.py, tests/test_dataset.py	CIFARDataset and get_dataset accept a custom data directory. CIFAR uses fixed synthetic data after network download failures, removes a partial archive when possible, and propagates archive and parsing errors. Tests cover fallback, archive and batch failures, valid loading and sampling, RNG state, and factory behavior.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Bug fix

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly summarizes the main change: CIFAR fallback now distinguishes network errors from corrupted archives and batches.
Docstring Coverage	✅ Passed	Docstring coverage is 80.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 15 functions across 2 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Actionable comments posted: 2

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• 🪄 Fix CodeRabbit comments on this PR

🤖 Prompt to fix review comments

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Inline comments:
Review comments at @src/dataset.py:
- Around line 32-38: Update the _NETWORK_ERRORS tuple to remove the broad
OSError entry while keeping its specific network exception types, so local
filesystem errors from _download propagate instead of triggering fallback data.
- Around line 227-233: Update the extraction call in the dataset download flow
to use Python’s data filter so symlink-based archive traversal is blocked, and
raise the declared Python minimum in pyproject.toml to 3.10.12 to match the
filter’s availability.

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📥 Commits

Reviewing files that changed from the base of the PR and between 14a21c4 and 5dc237e.

📒 Files selected for processing (2)

• src/dataset.py
• tests/test_dataset.py

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