https://github.com/atcold/torch-net-toolkit
A simple module for <Torch7> and the <nn> package
https://github.com/atcold/torch-net-toolkit
Last synced: 12 months ago
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A simple module for <Torch7> and the <nn> package
- Host: GitHub
- URL: https://github.com/atcold/torch-net-toolkit
- Owner: Atcold
- Created: 2014-03-31T18:34:21.000Z (about 12 years ago)
- Default Branch: master
- Last Pushed: 2015-04-30T13:57:43.000Z (almost 11 years ago)
- Last Synced: 2025-03-30T16:06:00.036Z (about 1 year ago)
- Language: Lua
- Size: 264 KB
- Stars: 18
- Watchers: 2
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# net-Toolkit
A simple module for [`Torch7`](https://github.com/torch/torch7) and the [`nn` package](https://github.com/torch/nn).
## Installation
```bash
luarocks install --server=https://raw.github.com/Atcold/net-toolkit/master net-toolkit
```
## Description
The package `net-toolkit` allows to save and retrive to/from disk a lighter version of the network that is being training. After `require('net-toolkit')`, you will have the following functions at your disposal:
- [`netToolkit.saveNet()`](#savenet)
- [`netToolkit.saveNetFields()`](#savenetfields)
- [`netToolkit.loadNet()`](#loadnet)
### `saveNet()`
`saveNet()` saves a lighter version of your current network, removing all unnecessary data from it (such as *gradients*, *activation units*' state and etc...) and returns a new couple of flattened *weights* and *gradients*. Usage:
```lua
w, dw = saveNet(fileName, model)
```
If you want to save the model in `ascii` format, call `saveNet()` as shown below. The output file will have an `.ascii` extension appended to `fileName`.
```lua
w, dw = saveNet(fileName, model, 'ascii')
```
### `saveNetFields()`
`saveNetFields()` saves your current network, removing all `Tensor` data you don't want to save and returns a new couple of flattened *weights* and *gradients*. (Set `format` to `'ascii'` for saving in `ascii` format.) Usage:
```lua
w, dw = saveNetFields(fileName, model, {'weight', 'bias'}, format)
```
In this case, only `weight` and `bias` `Tensor`s will be saved while the rest will be discarded. (The function `saveNet()` is, therefore, a shortcut to this specific usage of `saveNetFields()`.) However, we could have saved also `gradWeight` and `gradBias` by doing:
```lua
w, dw = saveNetFields(fileName, model, {'weight', 'bias', 'gradWeight', 'gradBias'}, format)
```
### `loadNet()`
Let's say we would like to load a network we have previously saved with `saveNet()` for continuing a training session on it. Some inner parameters (something about *gradients*) have to be restored, since `saveNet()` did a pruning operation on the network in order to save space. (Set `format` to `'ascii'` if you are trying to load a `.ascii` net. `fileName` does not have to include the `.ascii` extenstion.) Here is how we can handle this case:
```lua
model, w, dw = loadNet(fileName, format)
```
Now we can keep training, perhaps without forgetting to (re-)define a [*criterion* `loss`](https://github.com/torch/nn/blob/master/README.md#criterions) (the criterion is not saved with the network, so we have to re-define it, if we don't already do it somewhere else in the code).