Improve performance of OutputRecordingPass when processing QIR simulation results#3235
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…lation results This change updates the pattern used to process results in the `OutputRecordingPass` to avoid the perf hit from running Python `eval` for each result. This led to high overhead as each input needed to be parsed and processed by a fresh Python environment. Instead the code uses `eval` once to create a lambda for processing and then is able to invoke it directly on each result, speeding up processing.
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billti
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May 19, 2026
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May 19, 2026
The change in microsoft#3235 introduced a bug if the underlying simulation failed, which was caught by GPU tests post-merge. This changes the pattern to account for situations where the shot output might be empty.
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This change updates the pattern used to process results in the
OutputRecordingPassto avoid the perf hit from running Pythonevalfor each result. This led to high overhead as each input needed to be parsed and processed by a fresh Python environment. Instead the code usesevalonce to create a lambda for processing and then is able to invoke it directly on each result, speeding up processing.