Easily build your trainer for DNNs.
Project description
BuilT(Build a Trainer)
Easily build a trainer for your Depp Neural Network model and experiment as many as you want to find optimal combination of components(model, optimizer, scheduler) and hyper-parameters in a well-organized manner.
- No more boilerplate code to train and evaluate your DNN model. just focus on your model.
- Simply swap your dataset, model, optimizer and scheduler in the configuration file to find optimal combination. Your code doesn't need to be changed!!!.
- Support Cross Validation, OOF(Out of Fold) Prediction
- Support WandB(https://wandb.ai/) or tensorboard logging.
- Support checkpoint management(Save and load a model. Resume the previous training)
- BuilT easily integrates with Kaggle(https://www.kaggle.com/) notebook. (todo: add notebook link)
Installation
Please follow the instruction below to install BuilT.
Installation of BuilT package from the source code
git clone https://github.com/UoA-CARES/BuilT.git
cd BuilT
python setup.py install
Installation of BuilT package using pip
BuilT can be installed using pip(https://pypi.org/project/BuilT/).
pip install built
Usage
Configuration
Builder
Trainer
Dataset
Model
Loss
Optimizer
Scheduler
Logger
Metric
Inference
Ensemble
Examples
MNIST hand-written image classification
(todo)
Sentiment Classification
(todo)
Developer Guide
(todo)
conda create -n conda_BuilT python=3.7
conda activate conda_BuilT
pip install -r requirements.txt
Reference
Project details
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Source Distribution
BuilT-0.0.4.tar.gz
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Built Distributions
BuilT-0.0.4-py3.7.egg
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BuilT-0.0.4-py3-none-any.whl
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