aws / aws/sagemaker-python-sdk

SageMaker Bring Your Own Container on local mode - ProcessingOutput is not linked to local filesystem

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component: local mode component: pysdk-team Docker type: feature request
主要言語
Python
スター
2.3k
フォーク
1.3k
平均マージ
1日 22時間
マージ済み PR(30日)
35

説明

**Describe the feature you'd like**
During the work with SageMaker BYOC on local mode (with Python SDK), we encountered the situation where the outputs of the container are staged into the SageMaker default artifact bucket. Then the SDK does not download those artifacts into the local file system.

**How would this feature be used? Please describe.**
We want that SDK will download the artifacts created automatically into the local file system.

**Describe alternatives you've considered**
We had to create a mechanism to download those files by ourselves:
![Lack_of_impl_on_S3_outputs_download](https://user-images.githubusercontent.com/14873156/165520867-4f54f67c-b502-4250-98ae-b032a374d41c.png)
In the following snippet of code, we used [https://github.com/aws-samples/amazon-sagemaker-local-mode/blob/main/scikit_learn_bring_your_own_container_local_processing/scikit_learn_bring_your_own_container_local_processing.py ](https://github.com/aws-samples/amazon-sagemaker-local-mode/blob/main/scikit_learn_bring_your_own_container_local_processing/scikit_learn_bring_your_own_container_local_processing.py) as a reference (also used the output_config dictionary)

コントリビューションガイド

コントリビューションガイドを開く

調査の方向性

Start with the Python SDK's local-mode ProcessingOutput handling and the output_config dictionary described in the issue. Read the linked scikit_learn_bring_your_own_container_local_processing.py example as a behavioral reference; done means artifacts staged in the default SageMaker bucket are automatically downloaded to the local filesystem.

索引モデルが issue の本文から書いたものです。

評価

技術スタック
aws, python
領域
cloud, machine-learning
issue の種類
機能追加
難易度
4/5
見積もり時間
3〜5日
活発さ
停滞
明瞭さ
おおむね明確
初心者へのやさしさ
35/100

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