tinyframework

Introduction

Using pure numpy to construct deep learning computational graph framework.

note：To view the code, please switch to the master branch

Dev Tools：

• pycharm

Dependencies

• python: >= 3.7

Features

• Based on computational graph, can be used to build common machine learning models.
• Support automatic gradient.
• Support common optimization methods (such as GD, Momentum, Adagrad, RMSprop, Adam, etc.)
• Support common evaluation methods (such as Accuracy, Precision, AUC, F1_score, etc.)
• Support model save and load
• Support drawing calculate graph by pyecharts
• Support model serving by grpc
• Support model export
• Support distribute trainning.

logs：

To be added