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DiTEF - Distributed Task Execution Framework with Genetic Algorithm for Neural Network Architecture Search

Structure

  • producer/: all task producer components
    • backend/: task producer backend
      • genetic_algorithm/: implementation of genetic algorithm as task producer
      • genetic_individual/: producer individual implementations
      • shared/: code shared between genetic algorithm and individuals
    • frontend/: web interface of task producer
  • router/: central task router implementation
  • worker/: all task worker components
    • worker/: task worker (capable of executing evaluation code of worker individuals)
    • other directories: worker individual implementations (evaluation code)

Installation

DiTEF and Genetic Algorithm

The following packages should be installed on a central device/environment:

pip install --editable producer/backend/genetic_algorithm/sliding/
pip install --editable producer/backend/shared/
pip install --editable router/
yarn install --cwd producer/frontend/

The worker may be installed on all devices/environments that should act as workers:

pip install --editable worker/worker/

Individuals

For each individual type there exists a backend and worker part (the frontend is installed by default). The code can be installed from the following directories (replace ... with the individual type name):

pip install --editable producer/backend/genetic_individual/.../
pip install --editable worker/.../

Note: The directory name is not the individual type. The individual type is contained in the setup.py file (name field) within each directory.

The worker part of the neural network individual type has Tensorflow as a dependency. You may want to install this in a different environment (e.g. Docker image). We provide shell scripts for building a Docker image (see worker/genetic_individual_neuralnet/build.sh).

Custom individuals may be implemented in the aforementioned directories. This repository already contains individuals in producer/backend/genetic_individual/.

Additional Algorithms

Custom algorithms may be implemented and installed from directories in producer/backend/.

Usage

First, start the central task router:

ditef-router

Next, connect at least one task worker to the task router with the following arguments:

  1. Router URL, e.g. http://localhost:8080/
  2. Worker Individual Type (name field of setup.py in worker/.../ directory)

For example, for starting a worker for bitvector individual type:

ditef-worker http://localhost:8080/ ditef_worker_genetic_individual_bitvector

Start the sliding genetic algorithm task producer with the following arguments:

  1. Router URL, e.g. http://localhost:8080/
  2. Producer Individual Type (name field of setup.py in producer/backend/genetic_individual/.../ directory)
  3. Algorithm State Directory (will be created if it doesn't exist)

For example, for starting an algorithm for bitvector individual type:

ditef-producer-genetic-algorithm-sliding http://localhost:8080/ ditef_producer_genetic_individual_bitvector my_fancy_state

Start the frontend:

cd producer/frontend/
yarn start

After these steps, you can connect to the frontend and use the web interface.

License

MIT