Skip to main content

Convolutional Neural Netoworks Training Tools

Project description


Convolutional Neural Netoworks Training Tools

example of DenseNet training

The example is included in the bin folder in the package with the file name of

Here is a code snippet of creating a trainer and train the network given the model and the dataset.

from convtt.models import densenet
from convtt.train.trainer import *

# initialise trainer
optimiser = build_optimiser(model=model, name='ScheduledSGD', milestones=[10, 20], lr=0.1)
driver = build_driver(model=model, training_epoch=30, batch_size=128, training_data=dataset.train['images'],
                      validation_data=None, validation_label=None, test_data=dataset.test['images'],
                      test_label=dataset.test['labels'], optimiser=optimiser)
trainer = build_trainer(optimiser=optimiser, driver=driver)
test_acc = trainer.eval()

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

convtt-0.0.2.tar.gz (27.3 kB view hashes)

Uploaded source

Built Distribution

convtt-0.0.2-py3-none-any.whl (42.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page