Guideline to build framework

1.Define the scope and requirements of the framework:

Before you start building the framework, you need to define the problem domain, the target hardware platform, and the specific use cases that the framework will support. This will help you to narrow down the scope of the project and identify the key features and functionalities that the framework needs to provide.[]

2.Design the architecture of the framework:

Once you have defined the scope and requirements, you can start designing the architecture of the framework. This involves deciding on the programming languages, libraries, and tools that you will use, as well as the overall structure of the framework, such as the API, the data structures, and the algorithms.

3.Implement the core features of the framework:

With the architecture in place, you can start implementing the core features of the framework, such as the data preprocessing, the model training, the inference engine, and the hardware abstraction layer.

4.Optimize the performance of the framework:

To ensure that the framework runs efficiently on embedded and edge devices, you need to optimize the performance of the algorithms and the data structures. This may involve using specialized hardware accelerators, such as GPUs or FPGAs, or implementing custom optimization techniques, such as quantization or pruning.

5.Test and evaluate the framework:

Once you have implemented the core features and optimized the performance, you need to test and evaluate the framework to ensure that it meets the requirements and performs as expected. This involves running a series of tests and benchmarks on real-world data and hardware platforms