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narrow batch-size benchmark except to (RuntimeError, ValueError, TypeError, OSError) #396

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narrow batch-size benchmark except to (RuntimeError, ValueError, TypeError, OSError) #396

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2f5847b
narrow exception in model loading from Exception to (RuntimeError, Va…
May 28, 2026
ecc87c4
narrow batch-size benchmark except to (RuntimeError, ValueError, Type…
Jun 23, 2026
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2 changes: 1 addition & 1 deletion src/heretic/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -415,7 +415,7 @@ def run():
start_time = time.perf_counter()
responses = model.get_responses(prompts)
end_time = time.perf_counter()
except Exception as error:
except (RuntimeError, ValueError, TypeError, OSError) as error:
if batch_size == 1:
# Even a batch size of 1 already fails.
# We cannot recover from this.
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2 changes: 1 addition & 1 deletion src/heretic/model.py
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Expand Up @@ -148,7 +148,7 @@ def __init__(self, settings: Settings):
],
max_new_tokens=1,
)
except Exception as error:
except (RuntimeError, ValueError, TypeError) as error:

@gemini-code-assist gemini-code-assist Bot Jun 23, 2026

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medium

In src/heretic/model.py, the from_pretrained call can raise an OSError (for example, due to a network timeout, DNS failure, or a missing/corrupted file in the local cache). If the user has configured multiple dtypes (e.g., ["bfloat16", "float16"]) and the first one fails to load due to an OSError (e.g., because its files are not cached and the system is offline), the program will crash immediately instead of falling back to the next dtype (which might be fully cached and working). To ensure the robustness of the dtype fallback mechanism, OSError should also be caught here, similar to how it was added to the exception handler in src/heretic/main.py.

Suggested change
except (RuntimeError, ValueError, TypeError) as error:
except (RuntimeError, ValueError, TypeError, OSError) as error:

self.model = None # ty:ignore[invalid-assignment]
empty_cache()

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