ClearML/clearml
1
0
Fork 0
mirror of https://github.com/clearml/clearml synced 2025-02-07 13:23:40 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Allegro AI 2019-07-15 11:30:46 +03:00 committed by GitHub
parent 66e5d89268
commit df7e983cdd
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 44 additions and 29 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

49
README.md
View File

@ -20,33 +20,37 @@ your experimentation logs, outputs, and data to one centralized server.
(Experience TRAINS live at [https://demoapp.trainsai.io](https://demoapp.trainsai.io)) (Experience TRAINS live at [https://demoapp.trainsai.io](https://demoapp.trainsai.io))
![Alt Text](https://github.com/allegroai/trains/blob/master/docs/webapp_screenshots.gif?raw=true) ![Alt Text](https://github.com/allegroai/trains/blob/master/docs/webapp_screenshots.gif?raw=true)
## Main Features ## TRAINS Automatically Logs Everything
**With only two lines of code, this is what you are getting:**
* Seamless integration with leading frameworks, including: *PyTorch*, *TensorFlow*, *Keras*, and others coming soon * Git repository, branch, commit id and entry point (git diff coming soon)
* Support for *Jupyter Notebook* and *PyCharm* remote debugging * Hyper-parameters, including
* Automatic log collection. * ArgParser for command line parameters with currently used values
* Query, Filter, and Compare your experiment data and results * Tensorflow Defines (absl-py)
* Share and collaborate * Explicit parameters dictionary
* Initial model weights file
* Model snapshots
* stdout and stderr
* Tensorboard/TensorboardX scalars, metrics, histograms, images (with audio coming soon)
* Matplotlib & Seaborn
**Detailed overview of TRAINS offering and system design can be found [Here](https://github.com/allegroai/trains/blob/master/docs/brief.md).** **Detailed overview of TRAINS offering and system design can be found [Here](https://github.com/allegroai/trains/blob/master/docs/brief.md).**
## Using TRAINS ## Using TRAINS
We have a demo server up and running at https://demoapp.trainsai.io. You can try out TRAINS and test your code with it. TRAINS is a two part solution:
Note that it resets every 24 hours and all of the data is deleted.
When you are ready to use your own TRAINS server, go ahead and [install *TRAINS-server*](#configuring-your-own-trains). 1. TRAINS [python package](https://pypi.org/project/trains/) (auto-magically connects your code, see [Using TRAINS](https://github.com/allegroai/trains#using-trains))
**TRAINS requires only two lines of code for full integration.**
TRAINS requires only two lines of code for full integration.
To connect your code with TRAINS: To connect your code with TRAINS:
1. Install TRAINS - Install TRAINS
pip install trains pip install trains
2. Add the following lines to your code - Add the following lines to your code
from trains import Task from trains import Task
task = Task.init(project_name="my project", task_name="my task") task = Task.init(project_name="my project", task_name="my task")
@ -54,14 +58,26 @@ To connect your code with TRAINS:
* If project_name is not provided, the repository name will be used instead * If project_name is not provided, the repository name will be used instead
* If task_name (experiment) is not provided, the current filename will be used instead * If task_name (experiment) is not provided, the current filename will be used instead
3. Run your code. When TRAINS connects to the server, a link is printed. For example - Run your code. When TRAINS connects to the server, a link is printed. For example
TRAINS Results page: TRAINS Results page:
https://demoapp.trainsai.io/projects/76e5e2d45e914f52880621fe64601e85/experiments/241f06ae0f5c4b27b8ce8b64890ce152/output/log https://demoapp.trainsai.io/projects/76e5e2d45e914f52880621fe64601e85/experiments/241f06ae0f5c4b27b8ce8b64890ce152/output/log
4. Open the link and view your experiment parameters, model and tensorboard metrics - Open the link and view your experiment parameters, model and tensorboard metrics
## Configuring Your Own TRAINS 2. [TRAINS-server](https://github.com/allegroai/trains-server) for logging, querying, control and UI ([Web-App](https://github.com/allegroai/trains-web))
We have a demo server up and running at [https://demoapp.trainsai.io](https://demoapp.trainsai.io). You can try out TRAINS and test your code with it.
Note that it resets every 24 hours and all of the data is deleted.
When you are ready to use your own TRAINS server, go ahead and [install *TRAINS-server*](#configuring-your-own-trains).
System diagram of [TRAINS](https://github.com/allegroai/trains-server) in action
<img src="https://github.com/allegroai/trains/blob/master/docs/system_diagram.png?raw=true" width="30%">
## Configuring Your Own TRAINS server
1. Install and run *TRAINS-server* (see [Installing the TRAINS Server](https://github.com/allegroai/trains-server)) 1. Install and run *TRAINS-server* (see [Installing the TRAINS Server](https://github.com/allegroai/trains-server))
@ -112,4 +128,3 @@ See the TRAINS [Guidelines for Contributing](https://github.com/allegroai/trains
_May the force (and the goddess of learning rates) be with you!_ _May the force (and the goddess of learning rates) be with you!_