tfx.dsl.component.experimental.container_component.create_container_component

Creates a container-based component.

tfx.dsl.component.experimental.container_component.create_container_component(
    name: Text,
    image: Text,
    command: List[tfx.dsl.component.experimental.placeholders.CommandlineArgumentType],
    inputs: Dict[Text, Any] = None,
    outputs: Dict[Text, Any] = None,
    parameters: Dict[Text, Any] = None
) -> Callable[..., tfx.dsl.components.base.base_component.BaseComponent]

Args
name	The name of the component
image	Container image name.
command	Container entrypoint command-line. Not executed within a shell. The command-line can use placeholder objects that will be replaced at the compilation time. The placeholder objects can be imported from tfx.dsl.component.experimental.placeholders. Note that Jinja templates are not supported.
inputs	The list of component inputs
outputs	The list of component outputs
parameters	The list of component parameters

Returns
Component that can be instantiated and user inside pipeline.

Example:

component = create_container_component( name='TrainModel', inputs={ 'training_data': Dataset, }, outputs={ 'model': Model, }, parameters={ 'num_training_steps': int, }, image='gcr.io/my-project/my-trainer', command=[ 'python3', 'my_trainer', '--training_data_uri', InputUriPlaceholder('training_data'), '--model_uri', OutputUriPlaceholder('model'), '--num_training-steps', InputValuePlaceholder('num_training_steps'), ] )