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Below are the key features delivered in Adlik Release 0.1.0.

Model Compiler

  1. A new framework which is easy to expand and maintain.
  2. Compilation of models trained from Keras, Tensorflow and Pytorch for better execution on CPU/GPU.

Training framework

Model format

Target runtime

compiled format

Keras

h5

Tf Serving

SavedModel

 

 

OpenVINO

IR

 

 

TensorRT

Plan

 

 

TF-Lite

tflite

TensorFlow

Ckpt/pb

Tf Serving

SavedModel

 

 

OpenVINO

IR

 

 

TensorRT

Plan

 

 

TF-Lite

tflite

PyTorch

pth

OpenVINO

IR

 

 

TensorRT

Plan

 

Training frameworkInference engine

hardware environment

 

TensorFlow Serving-1.14

CPU/GPU

 

TensorFlow Serving-2.2

CPU/GPU

 

OpenVINO-2019

CPU

 

TensorRT-6

GPU

 

TensorRT-7

GPU

 

TF Lite-2.1

CPU(X86/ARM)

TensorFlow

TensorFlow Serving-1.14

CPU/GPU

 

TensorFlow Serving-2.2

CPU/GPU

 

OpenVINO-2019

CPU

 

TensorRT-6

GPU

 

TensorRT-7

GPU

 

TF Lite-2.1

CPU(X86/ARM)

PyTorch

OpenVINO-2019

CPU

 

TensorRT-6

GPU


Model Optimizer

  1. Multi nodes multi GPUs training and pruning.
  2. Configurable implementation of filter pruning to achieve smaller size of inference models.
  3. Small batch dataset quantization for TF-Lite and TF-TRT.

 

Inference Engine

  1. Management of multi models and multi versions.
  2. HTTP/GRPC interfaces for inference service.
  3. Runtime scheduler that supports scheduling of multi model instances.
  4. Integration of multiple DL inference runtime, including TensorFlow Serving, OpenVINO, TensorRT and TF Lite.

    Integrated Inference engine

    Hardware environment

    TensorFlow Serving-1.14

    CPU/GPU

    TensorFlow Serving-2.2

    CPU/GPU

    OpenVINO-2019

    CPU

    TensorRT-6

    GPU

    TensorRT-7

    GPU

    TF Lite-2.1

    CPU(X86/ARM)

  5. Integration of dlib to support ML runtime.

 

Benchmark Test Framework for Deep Learning Model

  1. A containalized solution which auto executes compiling, packaging of models, loading of runtime and models, startup of inference service and client, and generation of testing results.
  2. Supports all the compilers and runtime that can be integrated into Adlik.
  3. Supported output: inference result, inference speed, delay of inference execution.
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