Skip to content

Commit

Permalink
[Docs] Update model store documentation
Browse files Browse the repository at this point in the history
TODO: add a screenshot of the official model store once approved
  • Loading branch information
lukeyeager committed Dec 12, 2016
1 parent efcb35d commit cfc527b
Show file tree
Hide file tree
Showing 5 changed files with 77 additions and 52 deletions.
129 changes: 77 additions & 52 deletions docs/ModelStore.md
Original file line number Diff line number Diff line change
@@ -1,72 +1,97 @@
# Model Store


## Introduction
Model Store lists models in user-specified servers.
Users can imports models from Model Store into DIGITS.


## Setting up environment variable
The configuration of Model Store requires one environment variable DIGITS_MODEL_STORE_URL to be set.
NVIDIA plans to publish one public Model Store at http://developer.download.nvidia.com/compute/machine-learning/modelstore/4.5.0.
You can set up the environment variable with that url before launching DIGITS.
For example, run the following command in your Bash shell.
``` shell
export DIGITS_MODEL_STORE_URL='http://developer.download.nvidia.com/compute/machine-learning/modelstore/4.5.0'
```
If multiple model stores are available, specify their url's, separated by the comma (,).
``` shell
export DIGITS_MODEL_STORE_URL='http://localhost/mymodelstore,http://dlserver/teammodelstore'
```

DIGITS 5.0 introduces the concept of a "model store," which is a collection of trained models that can be used as pre-trained weights to accelerate training convergence.
A DIGITS server can be configured to connect to one or more model stores to download these trained models from the store to the server.

## Browse and import model
First launch DIGITS.
Click Pretrained Models tab, and select 'Retrieve from Model Store' under 'Load Model.'
The new page shows models available in model stores.
By default, DIGITS is configured to connect to the official NVIDIA model store.
See instructions below for creating and connecting to your own store[s].

![List models](images/model-store-list.png)
## Usage

Hover the Note field to show complete text.
Enter keyword in 'Filter list by' to limit results.
Click 'Update model list' button will retrieve the latest model list (see limitation).
Click 'Import' will import that model into DIGITS (may takes a few seconds, depends on network speed).
From the DIGITS home page, click on "Pretrained Models", then "Load Model" > "Images" > "Retreive from Model Store".

After successfully importing the model, DIGITS redirects the browser to Home page.
![Home page](images/model-store/home.jpg)

![Imported models](images/model-store-import.png)
On the model store page, you will see a list of all the models available for download.
Click on the small download icon (first column) to download a model from the store to the DIGITS server.

The Pretrained Models table will show the newly imported model.
At this moment, you can use that imported model like other pretrained models.
![Official store](images/model-store/official.jpg)

After downloading a model, you can return to the homepage to see the list of pretrained models.
To make use of the downloaded model for training, select it as a "Pretrained Network" in the "New Model" form.

## Create your own Model Store server
You can host your Model Store via Python's built-in SimpleHTTPServer.
First, in shell, cd to your own Model Store.
Then run the following command to start server at port 8000.
```
python -m SimpleHTTPServer 8000
```

At the top directory, create a master.json file (if your server does not support Apache directory listing).
The following is a sample master.json file.
You are welcome to create your own model store and use it to share models with others.
Here we will explain how to use Python's built-in SimpleHTTPServer to do it, but you can easily do the same thing with Apache or Nginx or whatever else you like.

Create a new directory on the server you'll be using for your store.
Collect some snapshot tarballs from DIGITS training jobs that you'd like to use for your store.
Unzip each tarball into its own directory (each should have a file called `info.json`).
Finally, create a file in the top directory called `master.json`.
```sh
$ cat master.json
{
"msg": "Luke's Model Store",
"children": [
"lenet",
"alexnet",
"googlenet",
"detectnet"
]
}
```
{"msg":"This is my own model store server.", "children":["Model01","Model02"]}
Your directory structure should look something like this:
```sh
$ tree -F
.
├── alexnet/
│   ├── deploy.prototxt
│   ├── info.json
│   ├── labels.txt
│   ├── mean.binaryproto
│   ├── snapshot_iter_11310.caffemodel
│   ├── solver.prototxt
│   └── train_val.prototxt
├── detectnet/
│   ├── deploy.prototxt
│   ├── info.json
│   ├── mean.binaryproto
│   ├── original.prototxt
│   ├── snapshot_iter_19140.caffemodel
│   ├── solver.prototxt
│   └── train_val.prototxt
├── googlenet/
│   ├── deploy.prototxt
│   ├── info.json
│   ├── labels.txt
│   ├── mean.binaryproto
│   ├── snapshot_iter_33450.caffemodel
│   ├── solver.prototxt
│   └── train_val.prototxt
├── lenet/
│   ├── deploy.prototxt
│   ├── info.json
│   ├── labels.txt
│   ├── mean.binaryproto
│   ├── snapshot_iter_28140.caffemodel
│   ├── solver.prototxt
│   └── train_val.prototxt
└── master.json
```
Model01 and Model02 are subdirectories containing the actual models.
Each model must at least include one info.json file, one weight file and one model file.
The info.json file is in the format of same file inside DIGITS downloaded model.
The subdirectory can optionally contain aux.json, which points to files not directly from DIGITS.
The following is a sample aux.json file.
Finally, use Python to start a server to serve these files
```sh
$ python -m SimpleHTTPServer
```
{"license": "3-clause BSD license", "logo": "logo.png", "dataset":"MNIST"}
Now, restart your DIGITS server and configure it to connect to your new server:
```sh
$ DIGITS_MODEL_STORE_URL=http://localhost:8000 ./digits-devserver
```
If `"license"` is defined, it will be shown on license field of that model.
The `license.txt` inside that subdirectory will be displayed when users clicking the license name.
`"logo"` is optional and once defined, DIGITS will display `logo.png` from the same subdirectory.

> NOTE: If you have installed DIGITS with a deb package, see [UbuntuInstall.md](UbuntuInstall.md) for instructions about how to reconfigure and restart your server.
When you have configured everything properly, you should see something like this:

## Limitation
Some web server may limit frequent requests from the same machine to stop malicious activities.
Therefore, DIGITS implemented a cache mechanism to reduce server-to-server communication.
The button, 'Update model list', invalidates cache and retrieve meta data from all models.
![Custom store](images/model-store/custom.jpg)
Binary file removed docs/images/model-store-import.png
Binary file not shown.
Binary file removed docs/images/model-store-list.png
Binary file not shown.
Binary file added docs/images/model-store/custom.jpg
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added docs/images/model-store/home.jpg
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.

0 comments on commit cfc527b

Please sign in to comment.