def _is_eligible_previous_execution(
self, current_execution: metadata_store_pb2.Execution,
target_execution: metadata_store_pb2.Execution) -> bool:
"""Compare if the previous execution is same as current execution.
This method will ignore ID and time related fields.
Args:
current_execution: the current execution.
target_execution: the previous execution to be compared with.
Returns:
whether the previous and current executions are the same.
"""
current_execution.properties['run_id'].string_value = ''
target_execution.properties['run_id'].string_value = ''
current_execution.id = target_execution.id
# Skip comparing time sensitive fields.
# The execution might not have the create_time_since_epoch or
# create_time_since_epoch field if the execution is created by an old
# version before this field is introduced.
if hasattr(current_execution, 'create_time_since_epoch'):
current_execution.ClearField('create_time_since_epoch')
if hasattr(target_execution, 'create_time_since_epoch'):
target_execution.ClearField('create_time_since_epoch')
if hasattr(current_execution, 'last_update_time_since_epoch'):
current_execution.ClearField('last_update_time_since_epoch')
if hasattr(target_execution, 'last_update_time_since_epoch'):
target_execution.ClearField('last_update_time_since_epoch')
return current_execution == target_execution
def _is_eligible_previous_execution(
self, currrent_execution: metadata_store_pb2.Execution,
target_execution: metadata_store_pb2.Execution) -> bool:
currrent_execution.properties['run_id'].string_value = ''
target_execution.properties['run_id'].string_value = ''
currrent_execution.id = target_execution.id
return currrent_execution == target_execution
def put_execution(
metadata_handler: metadata.Metadata,
execution: metadata_store_pb2.Execution,
contexts: Sequence[metadata_store_pb2.Context],
input_artifacts: Optional[typing_utils.ArtifactMultiMap] = None,
output_artifacts: Optional[typing_utils.ArtifactMultiMap] = None,
input_event_type: metadata_store_pb2.Event.Type = metadata_store_pb2.Event.
INPUT,
output_event_type: metadata_store_pb2.Event.Type = metadata_store_pb2.
Event.OUTPUT
) -> metadata_store_pb2.Execution:
"""Writes an execution-centric subgraph to MLMD.
This function mainly leverages metadata.put_execution() method to write the
execution centric subgraph to MLMD.
Args:
metadata_handler: A handler to access MLMD.
execution: The execution to be written to MLMD.
contexts: MLMD contexts to associated with the execution.
input_artifacts: Input artifacts of the execution. Each artifact will be
linked with the execution through an event with type input_event_type.
Each artifact will also be linked with every context in the `contexts`
argument.
output_artifacts: Output artifacts of the execution. Each artifact will be
linked with the execution through an event with type output_event_type.
Each artifact will also be linked with every context in the `contexts`
argument.
input_event_type: The type of the input event, default to be INPUT.
output_event_type: The type of the output event, default to be OUTPUT.
Returns:
An MLMD execution that is written to MLMD, with id pupulated.
"""
artifact_and_events = []
if input_artifacts:
artifact_and_events.extend(
_create_artifact_and_event_pairs(metadata_handler=metadata_handler,
artifact_dict=input_artifacts,
event_type=input_event_type))
if output_artifacts:
artifact_and_events.extend(
_create_artifact_and_event_pairs(metadata_handler=metadata_handler,
artifact_dict=output_artifacts,
event_type=output_event_type))
execution_id, artifact_ids, contexts_ids = (
metadata_handler.store.put_execution(
execution=execution,
artifact_and_events=artifact_and_events,
contexts=contexts,
reuse_context_if_already_exist=True))
execution.id = execution_id
for artifact_and_event, a_id in zip(artifact_and_events, artifact_ids):
artifact, _ = artifact_and_event
artifact.id = a_id
for context, c_id in zip(contexts, contexts_ids):
context.id = c_id
return execution