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Prevent Retraining of ExperimentalEmulator on Initialization #258

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@sweep-ai sweep-ai bot commented Jun 21, 2023

This PR addresses issue #243. The ExperimentalEmulator was being retrained every time it was initialized. This is not efficient and can lead to inconsistent results.

Changes made:

  • Added a condition in the train method of the ExperimentalEmulator class in summit/benchmarks/experimental_emulator.py to check if the emulator has already been trained. If it has, the retraining process is skipped.

This change will improve the efficiency of the ExperimentalEmulator and ensure consistent results across runs.

Fixes #243.

@marcosfelt marcosfelt closed this Jun 23, 2023
@marcosfelt marcosfelt deleted the sweep/issue-243-fix branch June 24, 2023 17:48
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Sweep: Emulator should not be retrained on initialization
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