如何删除训练定义？

Question

我正在试用用于神经网络的 Watson Studio 可视化建模器。在学习过程中，我尝试了几种不同的设计，并发表了几种训练定义。

如果我导航到 Experiment Builder，我会看到很多定义，有些是旧的，不再需要了。

如何删除旧的训练定义？（最好来自 Watson Studio UI）

Answer 1

Watson Machine Learning python client doesn't support deleting training run definitions. WML's python client API 显示支持的选项。不过，WML 团队正在努力添加此类删除功能。

同时，您可以使用WML's CLI tool执行bx ml delete:

NAME: delete - Delete a model/deployment/training-run/training-definitions/experiments/experiment-runs USAGE: bx ml delete models MODEL-ID bx ml delete deployments MODEL-ID DEPLOYMENT-ID bx ml delete training-runs TRAINING-RUN-ID bx ml delete training-definitions TRAINING-DEFINITION-ID bx ml delete experiments EXPERIMENT-ID bx ml delete experiment-runs EXPERIMENT-ID EXPERIMENT-RUN-ID

使用 bx ml list 获取有关您要删除的项目的详细信息：

Answer 2

实际上，python客户端支持删除训练定义。您只需调用 client.repository.delete(artifact_uid)。可以使用相同的方法从存储库中删除任何项目（模型、training_definition、实验）。它记录在 python 客户端文档 btw:

删除(artifact_uid)

Delete model, definition or experiment from repository.
Parameters: artifact_uid ({str_type}) – stored model, definition, or experiment UID

A way you might use me is:

>>> client.repository.delete(artifact_uid)

Training_run 与 training_definition 完全不同。如果需要，您也可以将其删除：

删除(run_uid)

Delete training run.
Parameters: run_uid ({str_type}) – ID of trained model

A way you might use me is:

>>> client.training.delete(run_uid)

如果需要，您还可以删除 experiment_run，方法是调用：

删除（实验_run_uid）

Delete experiment run.
Parameters: experiment_run_uid ({str_type}) – experiment run UID

A way you might use me is

>>> client.experiments.delete(experiment_run_uid)

请参阅 python 客户端文档以获取更多详细信息：http://wml-api-pyclient-dev.mybluemix.net/

如何删除训练定义？

How to delete training definitions?

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