What can Jittor do now ?

Model Definition & Training

This example shows how to model a two-layer neural network step by step and train from scratch In a few lines of Python code.

Basics: Op, Var

To train your model with jittor, there are only two main concept you need to know

Op: numpy like operator

Var: Basic data type of Jittor

Meta-operator

Meta-operator is a key concept of jittor, The hierarchical architecture of meta-operators is shown in this tutorial. The meta-operators are consist of reindex, reindex-reduce and element-wise operators.

Custom Op

In this tutorial, we will show

1.how to write your operator with C++ and CUDA and JIT compile it

2.execute your custom operation

Profiler

In this tutorial, we will show

1.how to profiling your model and check the elapsed time of each operation

2.profiling the cache hit rate

Jtune

(Coming soon)

Jtune is an optimization tool for developers to optimize ops, find op hotspots, and locate op performance bottlenecks.

Image Classification

Image classification refers to a process in computer vision that can classify an image according to its visual content. For example, an image classification algorithm may be designed to tell if an image contains a human figure or not. While detecting an object is trivial for humans, robust image classification is still a challenge in computer vision applications.

Semantic Segmentation

(Coming soon)

Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We can think of semantic segmentation as image classification at a pixel level.

Object Detection

(Coming soon)

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.

Image Generation

(Coming soon)

Image generation (synthesis) is the task of generating new images from an existing dataset.