🚀 Feature

Support google cloud storage (GCS) as storage backend - like S3 - so that this would work

import aim

run = aim.Run()
run.set_artifacts_uri('gs://my-bucket/artifacts/')
run.log_artifact('model.pt', name='trained-model')

Implementation should be straightforward using the google-cloud-storage package and implementing class GCSArtifactStorage(AbstractArtifactStorage) analogously to the S3 implementation.

Motivation

Allow both, S3 and GCS as storage backends for artifacts.