Nits

[mrzu]

While I was reading some of OpenAI code and documents, I noticed little typos/bugs. In my view, only the first of the three listed merits further scrutiny, as it appears the code may not align with the author's original intention. This is not an actual pull request.

1. eval_sample(self, sample: Any, *_)

Commit: Code flow nit in translate eval

Case when expected is None

In the case when expected is None, the code (line 45):

if isinstance(expected, tuple):
    expected = list(expected)
elif not isinstance(expected, list):
    expected = [expected]

Will have expected to hold [None] (a list with a single value None)

The code later checks if expected is not None (line 57) which will always be true, which I don't think was the intended behavior.

Case when score is None

When the score is evaluated by (line 58):

score = self.bleu.sentence_score(sampled, expected).score

If score is None, the line match = score > 30 (line 61) will produce the exception TypeError: '>' not supported between instances of 'NoneType' and 'int' and the following check score is not None (line 63) will never be reached.

2. find_top_k_closest_embeddings

Commit Factor the normalization in cosine similarity fn
Really a nit here, this is not a performance issue in practical terms. The normalization of the two input vectors can be combined.

3. Typo in the post Introducing Triton: Open-source GPU programming for neural networks

The section "Fused softmax with the Torch JIT.", provides the following code:

@torch.jit.script
def softmax(x):
    x_max = x.max(dim=1)[0]
    z = x - x_max[:, None]
    numerator = torch.exp(x)
    denominator = numerator.sum(dim=1)
    return numerator / denominator[:, None]

I believe numerator = torch.exp(x) should be numerator = torch.exp(z) (i.e. z not x)

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