From 024b0ead1b0839d3591bad3bdd3a6ab6bd20c381 Mon Sep 17 00:00:00 2001 From: Martin Kagamino Lehoux Date: Thu, 27 Aug 2026 12:10:55 +0200 Subject: Migrate to uv and Python 3.14 and add MNIST downloader to make the project runnable Context / Problem: setup.py + requirements.txt (Python 3.5) no longer install on modern Python, matplotlib missing from deps, main.py save/load broke on numpy 2.x (inhomogeneous array / allow_pickle), and demo required manual mnist.npy/data files. What: replace setup.py/requirements.txt with pyproject.toml (hatchling, PEP 621, requires-python >=3.10, classifiers 3.10-3.14), add .python-version 3.14 and uv.lock, add MultiLayerPerceptron/download.py (mlp-download) to fetch MNIST from storage.googleapis and generate data/train.npy, data/test.npy, mnist.npy, fix MultiLayerPerceptron/main.py layers class var and pickle handling with minimal changes, ignore .venv and track uv.lock, update README with uv workflow. QA: verified uv sync --all-groups, uv run mlp-download, uv run python -m MultiLayerPerceptron.main loads and trains, ruff check passes. --- MultiLayerPerceptron/main.py | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) (limited to 'MultiLayerPerceptron/main.py') diff --git a/MultiLayerPerceptron/main.py b/MultiLayerPerceptron/main.py index 2dbfa3d..d7a3138 100644 --- a/MultiLayerPerceptron/main.py +++ b/MultiLayerPerceptron/main.py @@ -49,9 +49,8 @@ class Layer(): self.grad_weights = np.outer(self.grad_inter, input) class MultiLayerPerceptron(): - layers = [] - def __init__(self, layer_sizes): + self.layers = [] for k in range(len(layer_sizes)-1): self.layers.append(Layer(layer_sizes[k], layer_sizes[k+1])) @@ -60,7 +59,8 @@ class MultiLayerPerceptron(): @staticmethod def load(filename): - array = np.load(open(filename, 'rb')) + with open(filename, 'rb') as f: + array = np.load(f, allow_pickle=True) sizes = [array[0].shape[1]] for layer in array: sizes.append(layer.shape[0]) @@ -70,8 +70,9 @@ class MultiLayerPerceptron(): return mlp def save(self, filename): - array = [layer.weights for layer in self.layers] - np.save(open(filename, 'wb'), array) + array = np.array([layer.weights for layer in self.layers], dtype=object) + with open(filename, 'wb') as f: + np.save(f, array, allow_pickle=True) def error(self, output, expected): return 1/2 * np.sum((expected - output)**2) @@ -171,10 +172,12 @@ if __name__ == "__main__": mlp = MultiLayerPerceptron.load('mnist.npy') print("OK") print("[Loading] Training set: ", end="") - space = np.load(open("data/train.npy", "rb")) + with open("data/train.npy", "rb") as f: + space = np.load(f, allow_pickle=True) space = [(input.reshape(28*28), expected) for input, expected in space] print("OK Testing set: ", end="") - test_space = np.load(open("data/test.npy", "rb")) + with open("data/test.npy", "rb") as f: + test_space = np.load(f, allow_pickle=True) test_space = [(input.reshape(28*28), expected) for input, expected in test_space] print("OK") -- cgit v1.3