[feat] S3ArtifactStorage custom boto3 client parameters

aim/storage/artifacts/s3_storage.py

@@ -71,3 +71,20 @@ def _get_s3_client(self):
 
         client = boto3.client('s3')
         return client
+
+
+def S3ArtifactStorage_factory(**boto3_client_kwargs: dict):
+    class S3ArtifactStorageCustom(S3ArtifactStorage):
+        def _get_s3_client(self):
+            import boto3, botocore
+            if 'config' in boto3_client_kwargs and isinstance(boto3_client_kwargs['config'], dict):
+                config_kwargs = boto3_client_kwargs.pop('config')
+                boto3_client_kwargs['config'] = botocore.config.Config(**config_kwargs)
+            client = boto3.client('s3', **boto3_client_kwargs)
+            return client
+    return S3ArtifactStorageCustom
+
+
+def S3ArtifactStorage_clientconfig(**boto3_client_kwargs: dict):
+    from aim.storage.artifacts import registry
+    registry.registry['s3'] = S3ArtifactStorage_factory(**boto3_client_kwargs)

docs/source/using/artifacts.md

@@ -47,10 +47,22 @@ Currently supported backends for artifacts storage are.
 
 #### S3 Artifacts Storage Backend
 
-Aim uses `boto3` Python package for accessing AWS resources. No additional credentials
-validation os done on the Aim side. More details on how credentials configuration is done
+Aim uses `boto3` Python package for accessing S3 resources. By default `boto3` targets AWS S3 resources. Connection and credential validation is handled by `boto3`. A typical way of supplying credentials for instance is by setting `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` environment variables.  More details on how configuration is done
 for `boto3` is available [here](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html).
 
+If you require direct control of how the `boto3` client handles your s3 connection, you may use `aim.storage.artifacts.s3_storage.S3ArtifactStorage_clientconfig(...)`. `S3ArtifactStorage_clientconfig` accepts any keyword-arguments that the `boto3.client` accepts, overwriting other means of boto3 configuration. This allows for the setting of credentials and connection details such as `endpoint_url` and `botocore` [Config](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html) parameters.
+
+```python
+import aim
+from aim.storage.artifacts.s3_storage import S3ArtifactStorage_clientconfig
+
+S3ArtifactStorage_clientconfig(aws_access_key_id=..., aws_secret_access_key=...,
+                               endpoint_url=..., config={'retries': {...}, },)
+run = aim.Run(...)
+run.set_artifacts_uri('s3://...')
+run.log_artifact(..., name=...)
+```
+
 #### File-system Artifacts Storage Backend
 
 Aim provides ability to use mounted FS as an artifact storage. Any kind of storage that provides a mounted FS