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quantization

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micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

  • Updated Jun 16, 2021
  • Python

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

  • Updated Jun 19, 2021
quic-ssiddego
quic-ssiddego commented Jul 16, 2021
  • Deprecate the usage of old quantsim implementation
  • Update bias correction implementation to use new quantsim api

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From a complexity perspective, this ticket is at an easy level.

maltanar
maltanar commented Mar 2, 2020

FINN has a Vivado version requirements, e.g. 2019.1 in the 0.2b release. The available Vivado version should be checked before any Vivado-related commands are launched, and an assertion should be raised if there is a version mismatch.

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