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GitHub - toodef/neural-pipeline: Neural networks training pipeline based on PyTo...
source link: https://github.com/toodef/neural-pipeline
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README.md
Neural Piepline
Neural networks training pipeline based on PyTorch. Designed to standardize training process and accelerate experiments.
- Core is about 2K lines, covered by tests, that you doesn't need to write again
- Flexible and customizable training process
- Checkpoints management and train process resuming (source and target device independent)
- Metrics processing and visualization by builtin (tensorboard, Matplotlib) or custom monitors
- Training best practices (e.g. learning rate decaying and hard negative mining)
- Metrics logging and comparison (DVC compatible)
Getting started:
Documentation
See the examples
- MNIST classification - notebook, file, Kaggle kernel
- Segmentation - notebook, file
- Resume training process - file
Neural Pipeline short overview:
import torch from neural_pipeline.builtin.monitors.tensorboard import TensorboardMonitor from neural_pipeline import DataProducer, AbstractDataset, TrainConfig, TrainStage,\ ValidationStage, Trainer, FileStructManager from somethig import MyNet, MyDataset fsm = FileStructManager(base_dir='data', is_continue=False) model = MyNet() train_dataset = DataProducer([MyDataset()], batch_size=4, num_workers=2) validation_dataset = DataProducer([MyDataset()], batch_size=4, num_workers=2) train_config = TrainConfig([TrainStage(train_dataset), ValidationStage(validation_dataset)], torch.nn.NLLLoss(), torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.5)) trainer = Trainer(model, train_config, fsm, torch.device('cuda:0')).set_epoch_num(50) trainer.monitor_hub.add_monitor(TensorboardMonitor(fsm, is_continue=False))\ .add_monitor(LogMonitor(fsm)) trainer.train()
This example of training MyNet on MyDataset with vizualisation in Tensorflow and with metrics logging for further experiments comparison.
Installation:
pip install neural-pipeline
For builtin module using install:
pip install tensorboardX matplotlib
Install latest version before it's published on PyPi
pip install -U git+https://github.com/toodef/neural-pipeline
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