[AutoPR machinelearningservices/resource-manager] update machine learning compute portion of the machine learning services swagger

azure-mgmt-machinelearningservices/HISTORY.rst

@@ -0,0 +1,9 @@
+.. :changelog:
+
+Release History
+===============
+
+0.1.0 (1970-01-01)
+++++++++++++++++++
+
+* Initial Release

azure-mgmt-machinelearningservices/MANIFEST.in

@@ -0,0 +1,2 @@
+include *.rst
+include azure_bdist_wheel.py

azure-mgmt-machinelearningservices/README.rst

@@ -0,0 +1,49 @@
+Microsoft Azure SDK for Python
+==============================
+
+This is the Microsoft Azure MyService Management Client Library.
+
+Azure Resource Manager (ARM) is the next generation of management APIs that
+replace the old Azure Service Management (ASM).
+
+This package has been tested with Python 2.7, 3.4, 3.5, 3.6 and 3.7.
+
+For the older Azure Service Management (ASM) libraries, see
+`azure-servicemanagement-legacy <https://pypi.python.org/pypi/azure-servicemanagement-legacy>`__ library.
+
+For a more complete set of Azure libraries, see the `azure <https://pypi.python.org/pypi/azure>`__ bundle package.
+
+
+Compatibility
+=============
+
+**IMPORTANT**: If you have an earlier version of the azure package
+(version < 1.0), you should uninstall it before installing this package.
+
+You can check the version using pip:
+
+.. code:: shell
+
+    pip freeze
+
+If you see azure==0.11.0 (or any version below 1.0), uninstall it first:
+
+.. code:: shell
+
+    pip uninstall azure
+
+
+Usage
+=====
+
+For code examples, see `MyService Management
+<https://docs.microsoft.com/python/api/overview/azure/>`__
+on docs.microsoft.com.
+
+
+Provide Feedback
+================
+
+If you encounter any bugs or have suggestions, please file an issue in the
+`Issues <https://github.com/Azure/azure-sdk-for-python/issues>`__
+section of the project.

azure-mgmt-machinelearningservices/azure/__init__.py

@@ -0,0 +1 @@
+__import__('pkg_resources').declare_namespace(__name__)

azure-mgmt-machinelearningservices/azure/mgmt/__init__.py

@@ -0,0 +1 @@
+__import__('pkg_resources').declare_namespace(__name__)

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py

@@ -34,6 +34,8 @@
     from .virtual_machine_ssh_credentials_py3 import VirtualMachineSshCredentials
     from .virtual_machine_properties_py3 import VirtualMachineProperties
     from .virtual_machine_py3 import VirtualMachine
+    from .hd_insight_properties_py3 import HDInsightProperties
+    from .hd_insight_py3 import HDInsight
     from .data_factory_py3 import DataFactory
     from .service_principal_credentials_py3 import ServicePrincipalCredentials
     from .compute_secrets_py3 import ComputeSecrets
@@ -64,6 +66,8 @@
     from .virtual_machine_ssh_credentials import VirtualMachineSshCredentials
     from .virtual_machine_properties import VirtualMachineProperties
     from .virtual_machine import VirtualMachine
+    from .hd_insight_properties import HDInsightProperties
+    from .hd_insight import HDInsight
     from .data_factory import DataFactory
     from .service_principal_credentials import ServicePrincipalCredentials
     from .compute_secrets import ComputeSecrets
@@ -103,6 +107,8 @@
     'VirtualMachineSshCredentials',
     'VirtualMachineProperties',
     'VirtualMachine',
+    'HDInsightProperties',
+    'HDInsight',
     'DataFactory',
     'ServicePrincipalCredentials',
     'ComputeSecrets',

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/aks.py

@@ -20,6 +20,8 @@ class AKS(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -52,6 +54,7 @@ class AKS(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/aks_py3.py

@@ -20,6 +20,8 @@ class AKS(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -52,6 +54,7 @@ class AKS(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -62,7 +65,7 @@ class AKS(Compute):
         'properties': {'key': 'properties', 'type': 'AKSProperties'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
-        super(AKS, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
+        super(AKS, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.properties = properties
         self.compute_type = 'AKS'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/azure_machine_learning_workspaces_enums.py

@@ -34,3 +34,4 @@ class ComputeType(str, Enum):
     batch_ai = "BatchAI"
     data_factory = "DataFactory"
     virtual_machine = "VirtualMachine"
+    hd_insight = "HDInsight"

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/batch_ai.py

@@ -20,6 +20,8 @@ class BatchAI(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class BatchAI(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/batch_ai_py3.py

@@ -20,6 +20,8 @@ class BatchAI(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class BatchAI(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,7 +66,7 @@ class BatchAI(Compute):
         'properties': {'key': 'properties', 'type': 'BatchAIProperties'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
-        super(BatchAI, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
+        super(BatchAI, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.properties = properties
         self.compute_type = 'BatchAI'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/compute.py

@@ -16,13 +16,15 @@ class Compute(Model):
     """Machine Learning compute object.
 
     You probably want to use the sub-classes and not this class directly. Known
-    sub-classes are: AKS, BatchAI, VirtualMachine, DataFactory
+    sub-classes are: AKS, BatchAI, VirtualMachine, HDInsight, DataFactory
 
     Variables are only populated by the server, and will be ignored when
     sending a request.
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class Compute(Model):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,11 +66,12 @@ class Compute(Model):
     }
 
     _subtype_map = {
-        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'DataFactory': 'DataFactory'}
+        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'HDInsight': 'HDInsight', 'DataFactory': 'DataFactory'}
     }
 
     def __init__(self, **kwargs):
         super(Compute, self).__init__(**kwargs)
+        self.compute_location = kwargs.get('compute_location', None)
         self.provisioning_state = None
         self.description = kwargs.get('description', None)
         self.created_on = None

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/compute_py3.py

@@ -16,13 +16,15 @@ class Compute(Model):
     """Machine Learning compute object.
 
     You probably want to use the sub-classes and not this class directly. Known
-    sub-classes are: AKS, BatchAI, VirtualMachine, DataFactory
+    sub-classes are: AKS, BatchAI, VirtualMachine, HDInsight, DataFactory
 
     Variables are only populated by the server, and will be ignored when
     sending a request.
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class Compute(Model):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,11 +66,12 @@ class Compute(Model):
     }
 
     _subtype_map = {
-        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'DataFactory': 'DataFactory'}
+        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'HDInsight': 'HDInsight', 'DataFactory': 'DataFactory'}
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, **kwargs) -> None:
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, **kwargs) -> None:
         super(Compute, self).__init__(**kwargs)
+        self.compute_location = compute_location
         self.provisioning_state = None
         self.description = description
         self.created_on = None

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/data_factory.py

@@ -20,6 +20,8 @@ class DataFactory(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -50,6 +52,7 @@ class DataFactory(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/data_factory_py3.py

@@ -20,6 +20,8 @@ class DataFactory(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -50,6 +52,7 @@ class DataFactory(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -59,6 +62,6 @@ class DataFactory(Compute):
         'compute_type': {'key': 'computeType', 'type': 'str'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, **kwargs) -> None:
-        super(DataFactory, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, **kwargs) -> None:
+        super(DataFactory, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.compute_type = 'DataFactory'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/hd_insight.py

@@ -0,0 +1,72 @@
+# 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 .compute import Compute
+
+
+class HDInsight(Compute):
+    """A HDInsight compute.
+
+    Variables are only populated by the server, and will be ignored when
+    sending a request.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
+    :ivar provisioning_state: The provision state of the cluster. Valid values
+     are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
+     values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
+     'Succeeded', 'Failed', 'Canceled'
+    :vartype provisioning_state: str or
+     ~azure.mgmt.machinelearningservices.models.ProvisioningState
+    :param description: The description of the Machine Learning compute.
+    :type description: str
+    :ivar created_on: The date and time when the compute was created.
+    :vartype created_on: datetime
+    :ivar modified_on: The date and time when the compute was last modified.
+    :vartype modified_on: datetime
+    :param resource_id: ARM resource id of the compute
+    :type resource_id: str
+    :ivar provisioning_errors: Errors during provisioning
+    :vartype provisioning_errors:
+     list[~azure.mgmt.machinelearningservices.models.MachineLearningServiceError]
+    :param compute_type: Required. Constant filled by server.
+    :type compute_type: str
+    :param properties:
+    :type properties:
+     ~azure.mgmt.machinelearningservices.models.HDInsightProperties
+    """
+
+    _validation = {
+        'provisioning_state': {'readonly': True},
+        'created_on': {'readonly': True},
+        'modified_on': {'readonly': True},
+        'provisioning_errors': {'readonly': True},
+        'compute_type': {'required': True},
+    }
+
+    _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
+        'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+        'description': {'key': 'description', 'type': 'str'},
+        'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
+        'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'},
+        'resource_id': {'key': 'resourceId', 'type': 'str'},
+        'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'},
+        'compute_type': {'key': 'computeType', 'type': 'str'},
+        'properties': {'key': 'properties', 'type': 'HDInsightProperties'},
+    }
+
+    def __init__(self, **kwargs):
+        super(HDInsight, self).__init__(**kwargs)
+        self.properties = kwargs.get('properties', None)
+        self.compute_type = 'HDInsight'