MDMM tests and hardware-aware metric functions#37
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ArghyaRanjanDas wants to merge 2 commits intocern-nextgen:mainfrom
Open
MDMM tests and hardware-aware metric functions#37ArghyaRanjanDas wants to merge 2 commits intocern-nextgen:mainfrom
ArghyaRanjanDas wants to merge 2 commits intocern-nextgen:mainfrom
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Tests cover metric functions, constraint functions, training phases, mask correctness, penalty numerical verification, constraint type variations, L0 mode variations, and edge cases.
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We can't merge directly to main branch unless it was merged to a dev one @ArghyaRanjanDas |
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Adds tests for the existing MDMM pruning method and integrates the hardware-aware metric functions (
FPGAAwareSparsityMetricandPACAPatternMetric) that were lost during intermediate branch merging.Also fixes a
float32/int32dtype bug inget_layer_sparsityon the TensorFlow backend.Supported backends
KERAS_BACKEND=tensorflowKERAS_BACKEND=torchTest files
pytest tests/test_mdmm.py tests/test_mdmm_metrics.py