aws / sagemaker-pytorch-inference-toolkit
Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
Summary
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| Main Code: 527 LOC (20 files) = PY (75%) + YML (19%) + C (3%) + IN (1%) + CFG (<1%) Secondary code: Test: 1,245 LOC (24); Generated: 0 LOC (0); Build & Deploy: 20 LOC (2); Other: 524 LOC (12); |
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| File Size: 0% long (>1000 LOC), 100% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 60% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 72% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (6 components) | ||
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2 years, 6 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2022-01-13
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3
commits
(30 days)
2
contributors
(30 days) |
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