https://github.com/crisbal/docker-torch-rnn

Docker images for using torch-rnn
https://github.com/crisbal/docker-torch-rnn

Last synced: 3 days ago
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Docker images for using torch-rnn

• Host: GitHub
• URL: https://github.com/crisbal/docker-torch-rnn
• Owner: crisbal
• Created: 2016-05-15T11:42:33.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-11-27T00:39:34.000Z (almost 4 years ago)
• Last Synced: 2024-08-02T05:07:12.088Z (3 months ago)
• Language: Dockerfile
• Homepage: https://hub.docker.com/r/crisbal/torch-rnn/
• Size: 13.7 KB
• Stars: 153
• Watchers: 10
• Forks: 36
• Open Issues: 9
• Metadata Files:
  • Readme: README.md

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README

        
# docker-torch-rnn

Docker images for using torch-rnn (https://github.com/jcjohnson/torch-rnn)

## Available tags

* `crisbal/torch-rnn:base`

    * Based on `ubuntu:14.04`

    * Allows usage of torch-rnn in CPU mode

* `lordalfred/docker-torch-rnn:cuda7.5`

    * Based on `nvidia/cuda:7.5-devel-ubuntu14.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 7.5 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

* `lordalfred/docker-torch-rnn:cuda8.0`

    * Based on `nvidia/cuda:8.0-devel-ubuntu16.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 8.0 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

* `lordalfred/docker-torch-rnn:cuda9.1`

    * Based on `nvidia/cuda:9.1-devel-ubuntu16.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 9.1 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

* `lordalfred/docker-torch-rnn:cuda9.2`

    * Based on `nvidia/cuda:9.2-devel-ubuntu16.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 9.2 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

* `lordalfred/docker-torch-rnn:cuda10.0` (**requires nvidia-docker v2**)

    * Based on `nvidia/cuda:10.0-devel-ubuntu16.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 10.0 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

* `lordalfred/docker-torch-rnn:10.0-ubuntu18.04` (**requires nvidia-docker v2**)

    * Based on `nvidia/cuda:10.0-devel-ubuntu18.04`

    * Allows usage of torch-rnn in GPU mode (Cuda 10.0 support)

    * Only run with nvidia-docker https://github.com/NVIDIA/nvidia-docker

## How to

More details here: https://github.com/jcjohnson/torch-rnn#usage

### CPU Only

1. Start bash in the container

    * `docker run --rm -ti crisbal/torch-rnn:base bash`

2. Preprocess the sample data

    ```

    python scripts/preprocess.py \

    --input_txt data/tiny-shakespeare.txt \

    --output_h5 data/tiny-shakespeare.h5 \

    --output_json data/tiny-shakespeare.json

    ```

3. Train

    ```

    th train.lua \

    -input_h5 data/tiny-shakespeare.h5 \

    -input_json data/tiny-shakespeare.json \

    -gpu -1

    ```

4. Sample

    * `th sample.lua -checkpoint cv/checkpoint_10000.t7 -length 2000 -gpu -1`

### CUDA

1. Install nvidia-docker

    * https://github.com/NVIDIA/nvidia-docker

2. Start bash in the container

    * `nvidia-docker run --rm -ti lordalfred/docker-torch-rnn:cuda10.0 bash`

3. Preprocess the sample data

    ```

    python scripts/preprocess.py \

    --input_txt data/tiny-shakespeare.txt \

    --output_h5 data/tiny-shakespeare.h5 \

    --output_json data/tiny-shakespeare.json

    ```

4. Train

    ```

    th train.lua \

    -input_h5 data/tiny-shakespeare.h5 \

    -input_json data/tiny-shakespeare.json

    ```

5. Sample

    * `th sample.lua -checkpoint cv/checkpoint_10000.t7 -length 2000`