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Krzysztof kuhy Rudnicki
1fd1de2f82
228 ruff findings to 0 across the notebook, its partial export and twm.py, and mypy --strict is clean on both .py files. A notebook is a deliverable that happens to contain code, so the check that mattered was not "does it still run" -- it needs a GPU, MNIST, CIFAR-10 and a slice of Quick, Draw! to run at all -- but "is anything except the code still exactly as submitted". Hashing every key of the .ipynb EXCEPT cell `source` gives 60242e116d12549d11c93f7f before the first edit and after the last one, across four passes and a `ruff format`. The file also round-trips byte-for-byte through json.dumps(indent=1, ensure_ascii=False), which is what made editing cells programmatically safe rather than a reformat of all 141 of them; the diff touches 38. print() became sys.stdout.write() rather than logging. In a notebook the print IS the output, and a logger with no handler configured would have silently emptied every cell -- the exact regression scripts/check_refactor_safety.py was written for. matprint's `print(x, end=" ")` and bare `print()` are preserved as writes with and without a trailing newline. Both `show_samples` and `show_samples_rgb` took (indices, preds, images, labels, count, names), which is six arguments and a mutable default. They now take a frozen `Samples` holding the last four, which also removed the same four-value tuple from seven call sites. Reviewing that diff is how I caught that I had transcribed `real_score = preds[sample][real_id]` as `samples.labels[sample]` -- a bug I introduced and then fixed before commit. Other real things, not just rule satisfaction: `np.in1d` is removed in NumPy 2 (NPY201) and is now `np.isin(...).ravel()`; `test_model` computed correct_indices and incorrect_indices and used neither; two cells grew `img` inside a loop so it was only bound by the `else` branch; and the Quick, Draw! downloader now builds a URL whose https scheme is a literal, which is what S310 was asking for. The README claimed the .py was "an nbconvert export of that notebook". It is an export of the CIFAR-10 section only -- 28 of 81 code cells -- and has been edited since. It says that now, and says the two are separate artifacts rather than one being regenerable from the other. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> |
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|---|---|---|
| .. | ||
| .gitignore | ||
| README.md | ||
| run.sh | ||
| TWM_KerasIntro.ipynb | ||
| TWM_KerasIntro.py | ||
| twm.py | ||
TWM — lab 4: introduction to Keras
Coursework for TWM (Techniki Wizyjne / machine vision), lab 4.
| Path | What it is |
|---|---|
TWM_KerasIntro.ipynb |
The submitted notebook — the deliverable. |
TWM_KerasIntro.py |
An nbconvert export of the notebook's CIFAR-10 section only. |
twm.py |
Prints the TensorFlow version the notebook will run against. |
The notebook is the source of truth. The .py is kept because it makes that
section's code reviewable and diffable, but it is not a full export: it covers
28 of the notebook's 81 code cells, all of them from the CIFAR-10 half, and it
has been edited since. Treat the two as separate artifacts rather than
regenerating one from the other.
Both need a GPU. The notebook's first cell calls sys.exit() when TensorFlow
reports no physical GPU device, and running it end to end downloads MNIST,
CIFAR-10 and a slice of the Quick, Draw! bitmaps into data/.