tfx.dsl.components.base.executor_spec.ExecutorClassSpec

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A specification of executor class.

Inherits From: ExecutorSpec

tfx.dsl.components.base.executor_spec.ExecutorClassSpec(
    executor_class: Type[tfx.dsl.components.base.base_executor.BaseExecutor]
)

Used in the notebooks

Used in the tutorials
Simple TFX Pipeline Tutorial using Penguin dataset Data validation using TFX Pipeline and TensorFlow Data Validation Model analysis using TFX Pipeline and TensorFlow Model Analysis Feature Engineering using TFX Pipeline and TensorFlow Transform

Attributes
executor_class	a subclass of base_executor.BaseExecutor used to execute this component (required).
extra_flags	extra flags to be set in the Python base executor.
class_path	Fully qualified class name for the executor class. .

Methods

add_extra_flags

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add_extra_flags(
    extra_flags: Iterable[str]
) -> None

copy

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copy() -> "ExecutorClassSpec"

Makes a copy of the ExecutorSpec.

An abstract method to implement to make a copy of the ExecutorSpec instance. Deepcopy is preferred in the implementation. But if for any reason a deepcopy is not able to be made because of some fields are not deepcopyable, it is OK to make a shallow copy as long as the subfield is consider globally immutable.

Returns
A copy of ExecutorSpec.

encode

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encode(
    component_spec: Optional[tfx.types.ComponentSpec] = None
) -> message.Message

Encodes ExecutorSpec into an IR proto for compiling.

This method will be used by DSL compiler to generate the corresponding IR.

Args
component_spec	Optional. The ComponentSpec to help with the encoding.

Returns
An executor spec proto.

from_json_dict

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@classmethod
from_json_dict(
    dict_data: Dict[Text, Any]
) -> Any

Convert from dictionary data to an object.

to_json_dict

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to_json_dict() -> Dict[Text, Any]

Convert from an object to a JSON serializable dictionary.