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-0.2.1b20230913.tar.gz (59.4 kB view details)

Uploaded Source

Built Distribution

autogluon.cloud-0.2.1b20230913-py3-none-any.whl (81.2 kB view details)

Uploaded Python 3

File details

Details for the file autogluon.cloud-0.2.1b20230913.tar.gz.

File metadata

File hashes

Hashes for autogluon.cloud-0.2.1b20230913.tar.gz
Algorithm Hash digest
SHA256 fd37c7145380b9aaaca24cd07a1c36f5decaeef89c1f8fbace303f54cd6eecfa
MD5 d31b50469394183b7f4563ea787294be
BLAKE2b-256 9ad10c5f752428a11a14ae9aa98ecd5477a495c893f4975f077e7a22e2c43b79

See more details on using hashes here.

File details

Details for the file autogluon.cloud-0.2.1b20230913-py3-none-any.whl.

File metadata

File hashes

Hashes for autogluon.cloud-0.2.1b20230913-py3-none-any.whl
Algorithm Hash digest
SHA256 db228163b805ba30767b665436a65add33ecae25e95714e7bd7e4b5ea45a5f76
MD5 ce89d6318ed9c7c93f8ee9b608683438
BLAKE2b-256 8985217e62930da7922e8660bdf03127f00bbf04ab374c2aba7d4c394eee6fcb

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