[WIP] Shot-allocation through sampling for split_non_commuting
#5832
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Hello. You may have forgotten to update the changelog!
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| shots_list = [ | ||
| binom(n=rmng_shots, p=prob).rvs() for rmng_shots in remaining_shots_budget[idx] |
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Are we certain the values we put in here are always bounded between 0 and 1 (including numerical precision errors)?
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| from pennylane.typing import Result, ResultBatch | |||
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| class ObsMetadata(NamedTuple): | |||
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Any advantage of using a NamedTuple vs a dataclass here?
| @transform | ||
| def split_non_commuting( | ||
| tape: qml.tape.QuantumScript, | ||
| grouping_strategy: Optional[str] = "default", | ||
| term_sampling: Optional[Literal["weighted", "uniform"]] = None, |
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Please can this term be included in the docs
… bug in post-processing function
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #5832 +/- ##
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- Coverage 99.67% 99.66% -0.02%
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Files 432 432
Lines 41839 41607 -232
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- Hits 41702 41466 -236
- Misses 137 141 +4 ☔ View full report in Codecov by Sentry. |
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Also @Shiro-Raven, please could you link the Shortcut story? |
Context:
Description of the Change:
Benefits:
Possible Drawbacks:
Related GitHub Issues:
[sc-64031]