Image#
- class pai.image.ImageInfo(image_name: str, image_uri: str, framework_name: str, image_scope: str, framework_version: Optional[str] = None, accelerator_type: Optional[str] = None, python_version: Optional[str] = None)#
基类:
object
This class represents information for an image provided by PAI.
- 参数:
image_name (str) -- The name of the image.
image_uri (str) -- The URI of the image.
framework_name (str) -- The name of the framework installed in the image.
framework_version (str, optional) -- The version of the framework (Default None).
image_scope (str) -- The scope of the image, could be 'training', 'inference' or 'develop'.
accelerator_type (str, optional) -- The type of accelerator. Defaults to None.
python_version (str, optional) -- The version of Python. Defaults to None.
- class pai.image.ImageScope#
基类:
object
Class containing constants that indicate the purpose of an image.
- TRAINING = 'training'#
Indicates the image is used for submitting a training job.
- INFERENCE = 'inference'#
Indicates the image is used for creating a prediction service.
- DEVELOP = 'develop'#
Indicates the image is used for running in DSW.
- classmethod to_image_label(scope: str)#
- pai.image.retrieve(framework_name: str, framework_version: str, accelerator_type: str = 'CPU', image_scope: Optional[str] = 'training', session: Optional[Session] = None) ImageInfo #
Get a container image URI that satisfies the specified requirements.
Examples:
# get a TensorFlow image with specific version for training. retrieve(framework_name="TensorFlow", framework_version="2.3") # get the latest PyTorch image that supports GPU for inference. retrieve( framework_name="PyTorch", framework_version="latest", accelerator_type="GPU", scope=ImageScope.INFERENCE, )
- 参数:
framework_name (str) -- The name of the framework. Possible values include TensorFlow, XGBoost, PyTorch, OneFlow, and others.
framework_version (str) -- The version of the framework to use. Get the latest version supported in PAI by set the parameters as 'latest'.
image_scope (str, optional) -- The scope of the image to use. Possible values include 'training', 'inference', and 'develop'.
accelerator_type (str, optional) -- The name of the accelerator to use. Possible values including 'CPU', and 'GPU', (Default CPU).
session (
pai.session.Session
, optional) -- A session object to interact with the PAI Service. If not provided, a default session will be used.
- 返回:
- A object contains information of the image that satisfy the
requirements.
- 返回类型:
- 抛出:
RuntimeError -- A RuntimeErrors is raised if the specific image is not found.
- pai.image.list_images(framework_name: str, session: Optional[Session] = None, image_scope: Optional[str] = 'training') List[ImageInfo] #
List available images provided by PAI.
- 参数:
framework_name (str) -- The name of the framework. Possible values include TensorFlow, XGBoost, PyTorch, OneFlow, and others.
image_scope (str, optional) -- The scope of the image to use. Possible values include 'training', 'inference', and 'develop'.
session (
pai.session.Session
) -- A session object used to interact with the PAI Service. If not provided, a default session is used.
- 返回:
A list of image URIs.
- 返回类型:
List[ImageInfo]