Adlik Antelope Release (V0.1.0)

Introduction of Adlik release 0.1.0: Adlik-加速AI应用落地的端到端工具链.pptx

Below are the key features delivered in Adlik Release 0.1.0, see chinese version here Feature List中文版. 

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.

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.