More SUT options in CLI #548
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MLCommons CLA bot All contributors have signed the MLCommons CLA ✍️ ✅ |
wpietri
approved these changes
Oct 2, 2024
| elif annotators: | ||
| if max_tokens is not None or temp is not None or top_p is not None or top_k is not None: |
| self._validate_file() | ||
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| def __iter__(self) -> Iterable[PromptWithContext]: | ||
| with open(self.path, newline="") as f: | ||
| csvreader = csv.DictReader(f) | ||
| for row in csvreader: | ||
| yield PromptWithContext( | ||
| prompt=TextPrompt(text=row["Text"]), | ||
| prompt=TextPrompt(text=row["Text"], options=self.sut_options), |
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It seems a little weird to me to have to set this for each prompt given that it's stable across the run, but I guess that's the object model we have for now.
| @@ -66,6 +68,33 @@ def test_run_sut_demos(sut): | |||
| assert re.search(r"Native response:", result.output) | |||
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| @patch("modelgauge.suts.demo_01_yes_no_sut.DemoYesNoSUT.translate_text_prompt") | |||
| def test_run_sut_with_options(mock_translate_text_prompt): | |||
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Good stuff. These CLI tests are kind of a pain to write, but I'm glad to see it.
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run-sutandrun-csv-itemsCLI commands now accept--temp,--max_tokens,--top-p, and--top-k.