Python SDK for Training Operator
Python 2.7 and 3.5+
pip install kubeflow-training
Then import the package:
from kubeflow import training
Install via Setuptools.
python setup.py install --user
(or sudo python setup.py install
to install the package for all users)
Please follow the sample to create, update and delete TFJob.
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 |