Add support for batched fairchem inference for many parallel jobs#3121
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zulissimeta wants to merge 20 commits intoQuantum-Accelerators:mainfrom
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Add support for batched fairchem inference for many parallel jobs#3121zulissimeta wants to merge 20 commits intoQuantum-Accelerators:mainfrom
zulissimeta wants to merge 20 commits intoQuantum-Accelerators:mainfrom
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Additional details and impacted files@@ Coverage Diff @@
## main #3121 +/- ##
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- Coverage 97.69% 96.28% -1.42%
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Files 97 97
Lines 4172 4248 +76
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+ Hits 4076 4090 +14
- Misses 96 158 +62 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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Summary of Changes
This PR adds support for FAIRChem batched inference via the
InferenceBatcherfromfairchem.core.calculate. This enables efficient GPU batching when running the same calculation (e.g., relaxations, static calculations) on many structures concurrently.Key additions:
New
map_partition_fairchembatchfunction insrc/quacc/wflow_tools/job_patterns.py:@jobthat processes a single partition (flat list) of atoms using FAIRChem batched inferenceNew
map_partitioned_lists_fairchembatchfunction insrc/quacc/wflow_tools/job_patterns.py:map_partition_fairchembatchjobsmap_partitioned_lists/map_partitionpatternNew
get_inference_batcherfunction insrc/quacc/recipes/mlp/_base.py:InferenceBatcherinstances keyed by model configurationshutdown_inference_batchers()for cleanupUpdated
pick_calculatorinsrc/quacc/recipes/mlp/_base.py:predict_unitkwarg to use batched inferencepredict_unitis provided for thread-safety during concurrent executionExample usage:
Tests:
Requirements
main).