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experiments/mnist/mnist_classifier_from_scratch.py

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@@ -35,7 +35,7 @@ def print_mean_std(name, v):
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# Always use np.float32, to avoid floating errors in descaling + stats.
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v = jsa.asarray(data, dtype=np.float32)
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m, s = np.mean(v), np.std(v)
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print(f"{name}: MEAN({m:.4f}) / STD({s:.4f}) / SCALE({scale.dtype})")
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print(f"{name}: MEAN({m:.4f}) / STD({s:.4f}) / SCALE({scale:.4f})")
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def init_random_params(scale, layer_sizes, rng=npr.RandomState(0)):

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