Skip to main content

Train and deploy AutoGluon backed models on the cloud

Project description

AutoGluon-Cloud

Continuous Integration

AutoGluon-Cloud aims to provide user tools to train, fine-tune and deploy AutoGluon backed models on the cloud. With just a few lines of codes, users could train a model and perform inference on the cloud without worrying about MLOps details such as resource management.

Currently, AutoGluon-Cloud supports AWS SageMaker as the cloud backend.

Example

# First install package from terminal:
# pip install -U pip
# pip install -U setuptools wheel
# pip install autogluon.cloud==0.2.0  # You don't need to install autogluon itself locally

from autogluon.cloud import TabularCloudPredictor
import pandas as pd
train_data = pd.read_csv("https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv")
test_data = pd.read_csv("https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv")
predictor_init_args = {"label": "class"}  # init args you would pass to AG TabularPredictor
predictor_fit_args = {"train_data": train_data, "time_limit": 120}  # fit args you would pass to AG TabularPredictor
cloud_predictor = TabularCloudPredictor(cloud_output_path='YOUR_S3_BUCKET_PATH')
cloud_predictor.fit(predictor_init_args=predictor_init_args, predictor_fit_args=predictor_fit_args)
cloud_predictor.deploy()
result = cloud_predictor.predict_real_time(test_data)
cloud_predictor.cleanup_deployment()
# Batch inference
result = cloud_predictor.predict(test_data)

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

autogluon.cloud-0.2.1b20230606.tar.gz (58.0 kB view details)

Uploaded Source

Built Distribution

autogluon.cloud-0.2.1b20230606-py3-none-any.whl (79.8 kB view details)

Uploaded Python 3

File details

Details for the file autogluon.cloud-0.2.1b20230606.tar.gz.

File metadata

File hashes

Hashes for autogluon.cloud-0.2.1b20230606.tar.gz
Algorithm Hash digest
SHA256 8cb9ae9ac93dcc138fec2585a7b364a47fc24d4c4474f1f3ddfaecc2cbdfb95f
MD5 0a44bb2451f289421dfea920938d0543
BLAKE2b-256 71e4705ef988f85fa65933ee5d36f2c4eb2a903275d20693843699eeddfcfa25

See more details on using hashes here.

File details

Details for the file autogluon.cloud-0.2.1b20230606-py3-none-any.whl.

File metadata

File hashes

Hashes for autogluon.cloud-0.2.1b20230606-py3-none-any.whl
Algorithm Hash digest
SHA256 eaa6c12f8ff65450aa84465dcb883f5d24891d8b4165143cb2d2f982781df871
MD5 da105b1a4d6ceb8d963a85c351368355
BLAKE2b-256 471c1473595f41747aa6a800b3c825f2ade03f276e4c7a284cd0f031a015c996

See more details on using hashes here.

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