CopyNet with TensorFlow 2.0
Project description
CopyNet implementation with TensorFlow 2
- Incorporating Copying Mechanism in Sequence-to-Sequence Learning
- Uses
TensorFlow 2.0
and above APIs withtf.keras
too - Adapted from AllenNLP's PyTorch implementation, their blog referenced below was very helpful to understand the math from an implementation perspective
Environment to run examples
Setup
- Copy
sample.env
to.env
and enter appropriate values for the variables - A brief description of each is provided as a comment in that file
- Post that run,
./setup-env.sh [--no-docker]
- Uses env file to configure project environment
- Builds required docker images (if you don't wanna use Docker then pass
--no-docker
option to thesetup-env.sh
script) - Makes a python environment and installes required packages in it
- Prepares an
lock.env
file. Do not edit/ delete it
Rebuilding environment
- You may change environment config in the process of development
- This includes adding a new python package to requirements.txt
- After changing run,
./setup-env.sh [--no-docker]
- If you do not want Docker, then pass
--no-docker
option similar to before
Start environment
- At the end of setup script you will be shown the commands to start the environments
- They are,
./start-env.sh nb # For Dockerized jupyter server ./start-env.sh bash # For Dockerized bash
- It is not necessary to use the
start-env.sh
script for virtualenv, the regularsource
command to activate it is enough
Note on Dockerized environment
- The dockerized environment is specifically helpful and recommended when
using
GPU
- It takes care of many nuances involved in setting up CUDA. Your host machine should just have correct NVIDIA drivers and nothing else
- It is recommended to run the examples in this environment to ensure all correct dependencies are met
Run examples
- Instructions to run an example are detailed in its own folders respectively
References
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
copynet-tf-0.2.0.tar.gz
(21.5 kB
view details)
Built Distribution
File details
Details for the file copynet-tf-0.2.0.tar.gz
.
File metadata
- Download URL: copynet-tf-0.2.0.tar.gz
- Upload date:
- Size: 21.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d4316f412c45375fe30cc533264d3321632280dac31a546f0ce8a361aa37598b |
|
MD5 | d7415cb0bd42d3aecafb340b2cd3be2f |
|
BLAKE2b-256 | 7d215942b8045a8c4c31d3f333283fcbffd45995dd61a61d86e77b33b88d0007 |
File details
Details for the file copynet_tf-0.2.0-py3-none-any.whl
.
File metadata
- Download URL: copynet_tf-0.2.0-py3-none-any.whl
- Upload date:
- Size: 25.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d2992ceb84048f7a5f8e105f37afead20cf89ec4cbdc25525e7692f1925aa693 |
|
MD5 | 411060b1138c9dfe95300b783676c087 |
|
BLAKE2b-256 | 8dd316f3a2df1445f98c077b5051cabf085a7a17ac49f51c523b839f3a246a45 |