# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from .execution_activity import ExecutionActivity
[docs]class AzureMLBatchExecutionActivity(ExecutionActivity):
"""Azure ML Batch Execution activity.
:param additional_properties: Unmatched properties from the message are
deserialized this collection
:type additional_properties: dict[str, object]
:param name: Activity name.
:type name: str
:param description: Activity description.
:type description: str
:param depends_on: Activity depends on condition.
:type depends_on: list[~azure.mgmt.datafactory.models.ActivityDependency]
:param type: Constant filled by server.
:type type: str
:param linked_service_name: Linked service reference.
:type linked_service_name:
~azure.mgmt.datafactory.models.LinkedServiceReference
:param policy: Activity policy.
:type policy: ~azure.mgmt.datafactory.models.ActivityPolicy
:param global_parameters: Key,Value pairs to be passed to the Azure ML
Batch Execution Service endpoint. Keys must match the names of web service
parameters defined in the published Azure ML web service. Values will be
passed in the GlobalParameters property of the Azure ML batch execution
request.
:type global_parameters: dict[str, object]
:param web_service_outputs: Key,Value pairs, mapping the names of Azure ML
endpoint's Web Service Outputs to AzureMLWebServiceFile objects specifying
the output Blob locations. This information will be passed in the
WebServiceOutputs property of the Azure ML batch execution request.
:type web_service_outputs: dict[str,
~azure.mgmt.datafactory.models.AzureMLWebServiceFile]
:param web_service_inputs: Key,Value pairs, mapping the names of Azure ML
endpoint's Web Service Inputs to AzureMLWebServiceFile objects specifying
the input Blob locations.. This information will be passed in the
WebServiceInputs property of the Azure ML batch execution request.
:type web_service_inputs: dict[str,
~azure.mgmt.datafactory.models.AzureMLWebServiceFile]
"""
_validation = {
'name': {'required': True},
'type': {'required': True},
}
_attribute_map = {
'additional_properties': {'key': '', 'type': '{object}'},
'name': {'key': 'name', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
'depends_on': {'key': 'dependsOn', 'type': '[ActivityDependency]'},
'type': {'key': 'type', 'type': 'str'},
'linked_service_name': {'key': 'linkedServiceName', 'type': 'LinkedServiceReference'},
'policy': {'key': 'policy', 'type': 'ActivityPolicy'},
'global_parameters': {'key': 'typeProperties.globalParameters', 'type': '{object}'},
'web_service_outputs': {'key': 'typeProperties.webServiceOutputs', 'type': '{AzureMLWebServiceFile}'},
'web_service_inputs': {'key': 'typeProperties.webServiceInputs', 'type': '{AzureMLWebServiceFile}'},
}
def __init__(self, name, additional_properties=None, description=None, depends_on=None, linked_service_name=None, policy=None, global_parameters=None, web_service_outputs=None, web_service_inputs=None):
super(AzureMLBatchExecutionActivity, self).__init__(additional_properties=additional_properties, name=name, description=description, depends_on=depends_on, linked_service_name=linked_service_name, policy=policy)
self.global_parameters = global_parameters
self.web_service_outputs = web_service_outputs
self.web_service_inputs = web_service_inputs
self.type = 'AzureMLBatchExecution'