September 30, 2019

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Neural networks training pipeline based on PyTorch

repo name toodef/neural-pipeline
repo link
language Python
size (curr.) 14351 kB
stars (curr.) 315
created 2018-12-14
license MIT License

Neural Pipeline

Neural networks training pipeline based on PyTorch. Designed to standardize training process and accelerate experiments.

Build Status Coverage Status Maintainability Gitter chat

  • Core is about 2K lines, covered by tests, that you don’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 Status

See the examples

Neural Pipeline short overview:

import torch

from neural_pipeline.builtin.monitors.tensorboard import TensorboardMonitor
from neural_pipeline.monitoring import LogMonitor
from neural_pipeline import DataProducer, TrainConfig, TrainStage,\
    ValidationStage, Trainer, FileStructManager

from somethig import MyNet, MyDataset

fsm = FileStructManager(base_dir='data', is_continue=False)
model = MyNet().cuda()

train_dataset = DataProducer([MyDataset()], batch_size=4, num_workers=2)
validation_dataset = DataProducer([MyDataset()], batch_size=4, num_workers=2)

train_config = TrainConfig(model, [TrainStage(train_dataset),
                                   ValidationStage(validation_dataset)], torch.nn.NLLLoss(),
                           torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.5))

trainer = Trainer(train_config, fsm, torch.device('cuda:0')).set_epoch_num(50)
trainer.monitor_hub.add_monitor(TensorboardMonitor(fsm, is_continue=False))\

This example of training MyNet on MyDataset with vizualisation in Tensorflow and with metrics logging for further experiments comparison.


PyPI version PyPI Downloads/Month PyPI Downloads

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+

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