def pipeline():
model_upload_op = ModelUploadOp(
project=self._project,
display_name=self._display_name,
serving_container_image_uri=self._serving_container_image_uri,
artifact_uri=self._artifact_uri
)
endpoint_create_op = EndpointCreateOp(
project=self._project,
display_name=self._display_name
)
model_deploy_op = ModelDeployOp(
project=self._project,
model=model_upload_op.outputs["model"]
)
batch_predict_op = ModelBatchPredictOp(
project=self._project,
model=model_upload_op.outputs["model"],
job_display_name=self._display_name,
gcs_source=self._gcs_source,
gcs_destination_prefix=self._gcs_destination_prefix
)
def pipeline():
model_upload_op = ModelUploadOp(
project=self._project,
display_name=self._display_name,
serving_container_image_uri=self._serving_container_image_uri,
artifact_uri=self._artifact_uri)
create_endpoint_op = EndpointCreateOp(
project=self._project,
location=self._location,
display_name=self._display_name)
model_deploy_op = ModelDeployOp(
model=model_upload_op.outputs["model"],
endpoint=create_endpoint_op.outputs["endpoint"],
deployed_model_display_name="deployed_model_display_name",
traffic_split={},
dedicated_resources_machine_type="n1-standard-4",
dedicated_resources_min_replica_count=1,
dedicated_resources_max_replica_count=2,
dedicated_resources_accelerator_type="fake-accelerator",
dedicated_resources_accelerator_count=1,
automatic_resources_min_replica_count=1,
automatic_resources_max_replica_count=2,
service_account="fake-sa",
explanation_metadata={"xai_m": "bar"},
explanation_parameters={"xai_p": "foo"},
)
_ = ModelUndeployOp(
model=model_upload_op.outputs["model"],
endpoint=create_endpoint_op.outputs["endpoint"],
).after(model_deploy_op)
def pipeline():
model_upload_op = ModelUploadOp(
project=self._project,
location=self._location,
display_name=self._display_name,
description="some description",
serving_container_image_uri=self._serving_container_image_uri,
serving_container_command=["command1", "command2"],
serving_container_args=["arg1", "arg2"],
serving_container_environment_variables=["env1", "env2"],
serving_container_ports=["123", "456"],
serving_container_predict_route=
"some serving_container_predict_route",
serving_container_health_route=
"some serving_container_health_route",
instance_schema_uri="some instance_schema_uri",
parameters_schema_uri="some parameters_schema_uri",
prediction_schema_uri="some prediction_schema_uri",
artifact_uri="some artifact_uri",
explanation_metadata={"xai_m": "bar"},
explanation_parameters={"xai_p": "foo"},
encryption_spec_key_name="some encryption_spec_key_name",
labels={"foo": "bar"})
_ = ModelDeleteOp(model=model_upload_op.outputs["model"], )
def pipeline():
model_upload_op = ModelUploadOp(
project=self._project,
display_name=self._display_name,
serving_container_image_uri=self._serving_container_image_uri,
artifact_uri=self._artifact_uri)
batch_predict_op = ModelBatchPredictOp(
project=self._project,
location=self._location,
job_display_name=self._display_name,
model=model_upload_op.outputs["model"],
instances_format="instance_format",
gcs_source_uris=[self._gcs_source],
bigquery_source_input_uri="bigquery_source_input_uri",
model_parameters={"foo": "bar"},
predictions_format="predictions_format",
gcs_destination_output_uri_prefix=self._gcs_destination_prefix,
bigquery_destination_output_uri=
"bigquery_destination_output_uri",
machine_type="machine_type",
accelerator_type="accelerator_type",
accelerator_count=1,
starting_replica_count=2,
max_replica_count=3,
manual_batch_tuning_parameters_batch_size=4,
generate_explanation=True,
explanation_metadata={"xai_m": "bar"},
explanation_parameters={"xai_p": "foo"},
encryption_spec_key_name="some encryption_spec_key_name",
labels={"foo": "bar"})
def pipeline():
model_upload_op = ModelUploadOp(
project=self._project,
display_name=self._display_name,
serving_container_image_uri=self._serving_container_image_uri,
artifact_uri=self._artifact_uri)
model_export_op = ModelExportOp(
model=model_upload_op.outputs["model"],
export_format_id="export_format",
artifact_destination="artifact_destination",
image_destination="image_destination")
