Hardware-Aware Neural Architecture Search with compression and compiler tuning
Project description
slimnet
Hardware-Aware Neural Architecture Search & Edge AI Deployment Toolkit
End-to-end pipeline to optimize deep learning models for embedded and edge hardware — from differentiable NAS to ONNX deployment.
Installation
pip install slimnet
Commands
# Full optimization pipeline
slimnet --model model.pth --platform local_pc --dataset cifar10
# Latency prediction
slimnet-predict --model model.onnx --platform local_pc
Stages
- Stage 1 — Differentiable NAS (MixedOp + Gumbel-Softmax)
- Stage 2 — Structured channel pruning
- Stage 3 — Post-Training Quantization (FP16 / INT8)
[opt-in] - Stage 4 — ORT compiler tuning
[opt-in]
License
MIT
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