# 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.
# --------------------------------------------------------------------------
import uuid
from msrest.pipeline import ClientRawResponse
from msrest.polling import LROPoller, NoPolling
from msrestazure.polling.arm_polling import ARMPolling
from .. import models
[docs]class MachineLearningComputeOperations(object):
"""MachineLearningComputeOperations operations.
You should not instantiate directly this class, but create a Client instance that will create it for you and attach it as attribute.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
:ivar api_version: Version of Azure Machine Learning resource provider API. Constant value: "2019-05-01".
"""
models = models
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.api_version = "2019-05-01"
self.config = config
[docs] def list_by_workspace(
self, resource_group_name, workspace_name, skiptoken=None, custom_headers=None, raw=False, **operation_config):
"""Gets computes in specified workspace.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param skiptoken: Continuation token for pagination.
:type skiptoken: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: An iterator like instance of ComputeResource
:rtype:
~azure.mgmt.machinelearningservices.models.ComputeResourcePaged[~azure.mgmt.machinelearningservices.models.ComputeResource]
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
def prepare_request(next_link=None):
if not next_link:
# Construct URL
url = self.list_by_workspace.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
if skiptoken is not None:
query_parameters['$skiptoken'] = self._serialize.query("skiptoken", skiptoken, 'str')
else:
url = next_link
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.get(url, query_parameters, header_parameters)
return request
def internal_paging(next_link=None):
request = prepare_request(next_link)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
return response
# Deserialize response
header_dict = None
if raw:
header_dict = {}
deserialized = models.ComputeResourcePaged(internal_paging, self._deserialize.dependencies, header_dict)
return deserialized
list_by_workspace.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes'}
[docs] def get(
self, resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config):
"""Gets compute definition by its name. Any secrets (storage keys, service
credentials, etc) are not returned - use 'keys' nested resource to get
them.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: ComputeResource or ClientRawResponse if raw=true
:rtype: ~azure.mgmt.machinelearningservices.models.ComputeResource or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
# Construct URL
url = self.get.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.get(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ComputeResource', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'}
def _create_or_update_initial(
self, resource_group_name, workspace_name, compute_name, parameters, custom_headers=None, raw=False, **operation_config):
# Construct URL
url = self.create_or_update.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(parameters, 'ComputeResource')
# Construct and send request
request = self._client.put(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200, 201]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
deserialized = None
header_dict = {}
if response.status_code == 200:
deserialized = self._deserialize('ComputeResource', response)
header_dict = {
'Azure-AsyncOperation': 'str',
}
if response.status_code == 201:
deserialized = self._deserialize('ComputeResource', response)
header_dict = {
'Azure-AsyncOperation': 'str',
}
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
client_raw_response.add_headers(header_dict)
return client_raw_response
return deserialized
[docs] def create_or_update(
self, resource_group_name, workspace_name, compute_name, parameters, custom_headers=None, raw=False, polling=True, **operation_config):
"""Creates or updates compute. This call will overwrite a compute if it
exists. This is a nonrecoverable operation. If your intent is to create
a new compute, do a GET first to verify that it does not exist yet.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param parameters: Payload with Machine Learning compute definition.
:type parameters:
~azure.mgmt.machinelearningservices.models.ComputeResource
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns ComputeResource or
ClientRawResponse<ComputeResource> if raw==True
:rtype:
~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.machinelearningservices.models.ComputeResource]
or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.machinelearningservices.models.ComputeResource]]
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
raw_result = self._create_or_update_initial(
resource_group_name=resource_group_name,
workspace_name=workspace_name,
compute_name=compute_name,
parameters=parameters,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
header_dict = {
'Azure-AsyncOperation': 'str',
}
deserialized = self._deserialize('ComputeResource', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
client_raw_response.add_headers(header_dict)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'}
def _update_initial(
self, resource_group_name, workspace_name, compute_name, scale_settings=None, custom_headers=None, raw=False, **operation_config):
parameters = models.ClusterUpdateParameters(scale_settings=scale_settings)
# Construct URL
url = self.update.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(parameters, 'ClusterUpdateParameters')
# Construct and send request
request = self._client.patch(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ComputeResource', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
[docs] def update(
self, resource_group_name, workspace_name, compute_name, scale_settings=None, custom_headers=None, raw=False, polling=True, **operation_config):
"""Updates properties of a compute. This call will overwrite a compute if
it exists. This is a nonrecoverable operation.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param scale_settings: Scale settings. Desired scale settings for the
amlCompute.
:type scale_settings:
~azure.mgmt.machinelearningservices.models.ScaleSettings
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns ComputeResource or
ClientRawResponse<ComputeResource> if raw==True
:rtype:
~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.machinelearningservices.models.ComputeResource]
or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.machinelearningservices.models.ComputeResource]]
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
raw_result = self._update_initial(
resource_group_name=resource_group_name,
workspace_name=workspace_name,
compute_name=compute_name,
scale_settings=scale_settings,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
deserialized = self._deserialize('ComputeResource', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'}
def _delete_initial(
self, resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers=None, raw=False, **operation_config):
# Construct URL
url = self.delete.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
query_parameters['underlyingResourceAction'] = self._serialize.query("underlying_resource_action", underlying_resource_action, 'str')
# Construct headers
header_parameters = {}
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.delete(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200, 202]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
header_dict = {
'Azure-AsyncOperation': 'str',
'Location': 'str',
}
client_raw_response.add_headers(header_dict)
return client_raw_response
[docs] def delete(
self, resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers=None, raw=False, polling=True, **operation_config):
"""Deletes specified Machine Learning compute.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param underlying_resource_action: Delete the underlying compute if
'Delete', or detach the underlying compute from workspace if 'Detach'.
Possible values include: 'Delete', 'Detach'
:type underlying_resource_action: str or
~azure.mgmt.machinelearningservices.models.UnderlyingResourceAction
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns None or
ClientRawResponse<None> if raw==True
:rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
raw_result = self._delete_initial(
resource_group_name=resource_group_name,
workspace_name=workspace_name,
compute_name=compute_name,
underlying_resource_action=underlying_resource_action,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
client_raw_response.add_headers({
'Azure-AsyncOperation': 'str',
'Location': 'str',
})
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}'}
[docs] def list_nodes(
self, resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config):
"""Get the details (e.g IP address, port etc) of all the compute nodes in
the compute.
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: AmlComputeNodesInformation or ClientRawResponse if raw=true
:rtype:
~azure.mgmt.machinelearningservices.models.AmlComputeNodesInformation
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
# Construct URL
url = self.list_nodes.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('AmlComputeNodesInformation', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list_nodes.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listNodes'}
[docs] def list_keys(
self, resource_group_name, workspace_name, compute_name, custom_headers=None, raw=False, **operation_config):
"""Gets secrets related to Machine Learning compute (storage keys, service
credentials, etc).
:param resource_group_name: Name of the resource group in which
workspace is located.
:type resource_group_name: str
:param workspace_name: Name of Azure Machine Learning workspace.
:type workspace_name: str
:param compute_name: Name of the Azure Machine Learning compute.
:type compute_name: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: ComputeSecrets or ClientRawResponse if raw=true
:rtype: ~azure.mgmt.machinelearningservices.models.ComputeSecrets or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`MachineLearningServiceErrorException<azure.mgmt.machinelearningservices.models.MachineLearningServiceErrorException>`
"""
# Construct URL
url = self.list_keys.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'computeName': self._serialize.url("compute_name", compute_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.MachineLearningServiceErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ComputeSecrets', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listKeys'}