| commit | cd6a929e30b9049ce16535ba43a223c5d3dd71cd | [log] [tgz] |
|---|---|---|
| author | Nick Kreeger <kreeger@google.com> | Fri Jun 12 13:25:37 2020 -0700 |
| committer | TensorFlower Gardener <gardener@tensorflow.org> | Fri Jun 12 13:39:35 2020 -0700 |
| tree | 5f251af54ac3122241db2e9dfb27105665ec45e1 | |
| parent | 3dd8cb721adf5505f8760fa48875a151d700b749 [diff] |
Track variable tensor buffer allocation in the "recording" MicroAllocator. The RecordingMicroAllocator class currently doesn't track variable tensor allocations. This was noted why the measured allocations had a missing ~10kb of tail space unaccounted for in the keyword model. This change tracks variable tensor allocation for the keyword model (the test conv model does not have any variable tensors). Total and tail allocation creep up a bit here to handle the additional fields in RecordingMicroAllocator: TestKeywordModelMemoryThreshold: ------------------------------- [RecordingMicroAllocator] Arena allocation total 21472 bytes [RecordingMicroAllocator] Arena allocation head 672 bytes [RecordingMicroAllocator] Arena allocation tail 20800 bytes [RecordingMicroAllocator] 'TfLiteTensor struct' used 6048 bytes with alignment overhead (requested 6048 bytes for 54 tensors) [RecordingMicroAllocator] 'TfLiteTensor quantization data' used 2160 bytes with alignment overhead (requested 2160 bytes for 162 allocations) [RecordingMicroAllocator] 'TfLiteTensor variable buffer data' used 10240 bytes with alignment overhead (requested 10240 bytes for 7 allocations) [RecordingMicroAllocator] 'NodeAndRegistration struct' used 1200 bytes with alignment overhead (requested 1200 bytes for 15 NodeAndRegistration structs) [RecordingMicroAllocator] 'Operator runtime data' used 148 bytes with alignment overhead (requested 148 bytes for 13 OpData structs) TestConvModelMemoryThreshold: ----------------------------- [RecordingMicroAllocator] Arena allocation total 12128 bytes [RecordingMicroAllocator] Arena allocation head 7744 bytes [RecordingMicroAllocator] Arena allocation tail 4384 bytes [RecordingMicroAllocator] 'TfLiteTensor struct' used 1680 bytes with alignment overhead (requested 1680 bytes for 15 tensors) [RecordingMicroAllocator] 'TfLiteTensor quantization data' used 1216 bytes with alignment overhead (requested 1216 bytes for 36 allocations) [RecordingMicroAllocator] 'TfLiteTensor variable buffer data' used 0 bytes with alignment overhead (requested 0 bytes for 0 allocations) [RecordingMicroAllocator] 'NodeAndRegistration struct' used 560 bytes with alignment overhead (requested 560 bytes for 7 NodeAndRegistration structs) [RecordingMicroAllocator] 'Operator runtime data' used 136 bytes with alignment overhead (requested 136 bytes for 5 OpData structs) PiperOrigin-RevId: 316166016 Change-Id: I7d806f901b39e5d6a73c3baaf11d85fa7f6e17b1
Documentation |
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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
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| Linux AMD ROCm GPU Stable Release | Release 1.15 / 2.x | |
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| Linux s390x CPU Stable Release | Release | |
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