ParallelTask Class

Parallel task.

Inheritance

azure.ai.ml.entities._mixins.RestTranslatableMixin

ParallelTask

azure.ai.ml.entities._mixins.DictMixin

ParallelTask

Constructor

ParallelTask(*, type: str | None = None, code: str | None = None, entry_script: str | None = None, program_arguments: str | None = None, model: str | None = None, append_row_to: str | None = None, environment: Environment | str | None = None, **kwargs: Any)

Parameters

Name	Description
type Required	str The type of the parallel task. Possible values are 'run_function'and 'model'.
code Required	str A local or remote path pointing at source code.
entry_script Required	str User script which will be run in parallel on multiple nodes. This is specified as a local file path. The entry_script should contain two functions: init(): this function should be used for any costly or common preparation for subsequent inferences, e.g., deserializing and loading the model into a global object. run(mini_batch): The method to be parallelized. Each invocation will have one mini-batch. 'mini_batch': Batch inference will invoke run method and pass either a list or a Pandas DataFrame as an argument to the method. Each entry in min_batch will be a filepath if input is a FileDataset, a Pandas DataFrame if input is a TabularDataset. run() method should return a Pandas DataFrame or an array. For append_row output_action, these returned elements are appended into the common output file. For summary_only, the contents of the elements are ignored. For all output actions, each returned output element indicates one successful inference of input element in the input mini-batch. Each parallel worker process will call init once and then loop over run function until all mini-batches are processed.
program_arguments Required	str The arguments of the parallel task.
model Required	str The model of the parallel task.
append_row_to Required	str All values output by run() method invocations will be aggregated into one unique file which is created in the output location. if it is not set, 'summary_only' would invoked, which means user script is expected to store the output itself.
environment Required	Union[Environment, str] Environment that training job will run in.

Keyword-Only Parameters

Name	Description
type Required
code Required
entry_script Required
program_arguments Required
model Required
append_row_to Required
environment Required

Methods

get
has_key
items
keys
update
values

get

get(key: Any, default: Any | None = None) -> Any

Parameters

Name	Description
key Required
default	Default value: None

has_key

has_key(k: Any) -> bool

Parameters

Name	Description
k Required

items

items() -> list

keys

keys() -> list

update

update(*args: Any, **kwargs: Any) -> None

values

values() -> list