Closed NoureldinYosri closed 4 months ago
Attention: Patch coverage is 98.63014%
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Project coverage is 97.81%. Comparing base (
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Files | Patch % | Lines |
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cirq-core/cirq/work/multiprocessing.py | 97.91% | 1 Missing :warning: |
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closing in favor of using tqmd.contrib.concurrent
Some code in
experiments
usesmultiprocessing.Pool
orThreadPoolExecutor
+ there are places that could benefit from using either to speed things up. The methods introduced in this PR standardize the way this is done and runs the batches with a progress bar which would improve UX since batching/threading/multiprocessing is used when running long running processes so getting a progress bar is a nice feature.