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Alex LembiyeuskiandGitHub
3daf40fe6a
* Add Python SDK for Kubeflow Training Operator * Update example notebooks * Update SDK generation tooling and docs * Re-generate SDK * Allow to specify container name in 'get_logs' methods * Generalize job labels * Check if attribute exists * Address code review comments
Kubeflow Training SDK
Python SDK for Training Operator
Requirements.
Python 2.7 and 3.5+
Installation & Usage
pip install
pip install kubeflow-training
Then import the package:
from kubeflow import training
Setuptools
Install via Setuptools.
python setup.py install --user
(or sudo python setup.py install to install the package for all users)
Getting Started
Please follow the sample to create, update and delete TFJob.
Documentation for API Endpoints
| Class | Method | Description |
|---|---|---|
| TFJobClient | create | Create TFJob |
| TFJobClient | get | Get or watch the specified TFJob or all TFJob in the namespace |
| TFJobClient | patch | Patch the specified TFJob |
| TFJobClient | delete | Delete the specified TFJob |
| TFJobClient | wait_for_job | Wait for the specified job to finish |
| TFJobClient | wait_for_condition | Waits until any of the specified conditions occur |
| TFJobClient | get_job_status | Get the TFJob status |
| TFJobClient | is_job_running | Check if the TFJob status is Running |
| TFJobClient | is_job_succeeded | Check if the TFJob status is Succeeded |
| TFJobClient | get_pod_names | Get pod names of TFJob |
| TFJobClient | get_logs | Get training logs of the TFJob |
| PyTorchJobClient | create | Create PyTorchJob |
| PyTorchJobClient | get | Get the specified PyTorchJob or all PyTorchJob in the namespace |
| PyTorchJobClient | patch | Patch the specified PyTorchJob |
| PyTorchJobClient | delete | Delete the specified PyTorchJob |
| PyTorchJobClient | wait_for_job | Wait for the specified job to finish |
| PyTorchJobClient | wait_for_condition | Waits until any of the specified conditions occur |
| PyTorchJobClient | get_job_status | Get the PyTorchJob status |
| PyTorchJobClient | is_job_running | Check if the PyTorchJob running |
| PyTorchJobClient | is_job_succeeded | Check if the PyTorchJob Succeeded |
| PyTorchJobClient | get_pod_names | Get pod names of PyTorchJob |
| PyTorchJobClient | get_logs | Get training logs of the PyTorchJob |