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gpt5.5/fable
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@@ -38,7 +38,7 @@ with torch.no_grad():
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# If init loss >> expected: wrong loss fn, bad init, or data pipeline broken
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```
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**Overfit-one-batch test**
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**Overfit-one-batch test** [Ng / torch lightning]
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```python
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model.train()
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batch = next(iter(train_loader))
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@@ -112,7 +112,7 @@ with torch.no_grad():
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# If very different: model sees real signal. Problem is elsewhere.
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```
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**NaN poisoning (leakage tracer)** [Wassname; forward-pass dual of Karpathy's gradient check below]
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**NaN poisoning (leakage tracer)** [Wassname
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```python
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# Leakage can hide anywhere: normalization fit on the full dataset, target
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# leaking into features, window functions peeking ahead, bad splits. Instead
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