class Azure::MachineLearningServices::Mgmt::V2018_11_19::MachineLearningCompute
These APIs allow end users to operate on Azure
Machine Learning Workspace resources.
Attributes
@return [MachineLearningServicesClient] reference to the MachineLearningServicesClient
Public Class Methods
Creates and initializes a new instance of the MachineLearningCompute
class. @param client service class for accessing basic functionality.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 18 def initialize(client) @client = client end
Public Instance Methods
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ComputeResource] Payload with Machine Learning compute definition. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeResource] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 604 def begin_create_or_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) response = begin_create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! response.body unless response.nil? end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ComputeResource] Payload with Machine Learning compute definition. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 645 def begin_create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? fail ArgumentError, 'parameters is nil' if parameters.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() request_content = @client.serialize(request_mapper, parameters) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:put, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 || status_code == 201 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end # Deserialize Response if status_code == 201 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ComputeResource] Payload with Machine Learning compute definition. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 625 def begin_create_or_update_with_http_info(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) begin_create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! end
Deletes specified Machine Learning compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param underlying_resource_action [UnderlyingResourceAction] Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'. Possible values include: 'Delete', 'Detach' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 851 def begin_delete(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) response = begin_delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:custom_headers).value! nil end
Deletes specified Machine Learning compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param underlying_resource_action [UnderlyingResourceAction] Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'. Possible values include: 'Delete', 'Detach' @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 890 def begin_delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? fail ArgumentError, 'underlying_resource_action is nil' if underlying_resource_action.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version,'underlyingResourceAction' => underlying_resource_action}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:delete, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 || status_code == 202 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? result end promise.execute end
Deletes specified Machine Learning compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param underlying_resource_action [UnderlyingResourceAction] Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'. Possible values include: 'Delete', 'Detach' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 871 def begin_delete_with_http_info(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) begin_delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:custom_headers).value! end
Updates properties of a compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ClusterUpdateParameters] Additional parameters for cluster update. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeResource] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 734 def begin_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) response = begin_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! response.body unless response.nil? end
Updates properties of a compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ClusterUpdateParameters] Additional parameters for cluster update. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 773 def begin_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? fail ArgumentError, 'parameters is nil' if parameters.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? # Serialize Request request_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ClusterUpdateParameters.mapper() request_content = @client.serialize(request_mapper, parameters) request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version}, body: request_content, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:patch, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Updates properties of a compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ClusterUpdateParameters] Additional parameters for cluster update. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 754 def begin_update_with_http_info(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) begin_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ComputeResource] Payload with Machine Learning compute definition. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeResource] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 245 def create_or_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) response = create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! response.body unless response.nil? end
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ComputeResource] Payload with Machine Learning compute definition. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] promise which provides async access to http response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 263 def create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) # Send request promise = begin_create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers) promise = promise.then do |response| # Defining deserialization method. deserialize_method = lambda do |parsed_response| result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() parsed_response = @client.deserialize(result_mapper, parsed_response) end # Waiting for response. @client.get_long_running_operation_result(response, deserialize_method) end promise end
Deletes specified Machine Learning compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param underlying_resource_action [UnderlyingResourceAction] Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'. Possible values include: 'Delete', 'Detach' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 345 def delete(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) response = delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:custom_headers).value! nil end
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param underlying_resource_action [UnderlyingResourceAction] Delete the underlying compute if 'Delete', or detach the underlying compute from workspace if 'Detach'. Possible values include: 'Delete', 'Detach' @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] promise which provides async access to http response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 364 def delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) # Send request promise = begin_delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:custom_headers) promise = promise.then do |response| # Defining deserialization method. deserialize_method = lambda do |parsed_response| end # Waiting for response. @client.get_long_running_operation_result(response, deserialize_method) end promise end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeResource] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 138 def get(resource_group_name, workspace_name, compute_name, custom_headers:nil) response = get_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! response.body unless response.nil? end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 173 def get_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
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 [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 156 def get_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) get_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! end
Gets computes in specified workspace.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param skiptoken [String] Continuation token for pagination. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Array<ComputeResource>] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 37 def list_by_workspace(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) first_page = list_by_workspace_as_lazy(resource_group_name, workspace_name, skiptoken:skiptoken, custom_headers:custom_headers) first_page.get_all_items end
Gets computes in specified workspace.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param skiptoken [String] Continuation token for pagination. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [PaginatedComputeResourcesList] which provide lazy access to pages of the response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1133 def list_by_workspace_as_lazy(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) response = list_by_workspace_async(resource_group_name, workspace_name, skiptoken:skiptoken, custom_headers:custom_headers).value! unless response.nil? page = response.body page.next_method = Proc.new do |next_page_link| list_by_workspace_next_async(next_page_link, custom_headers:custom_headers) end page end end
Gets computes in specified workspace.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param skiptoken [String] Continuation token for pagination. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 70 def list_by_workspace_async(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name}, query_params: {'api-version' => @client.api_version,'$skiptoken' => skiptoken}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::PaginatedComputeResourcesList.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Gets computes in specified workspace.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [PaginatedComputeResourcesList] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 947 def list_by_workspace_next(next_page_link, custom_headers:nil) response = list_by_workspace_next_async(next_page_link, custom_headers:custom_headers).value! response.body unless response.nil? end
Gets computes in specified workspace.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 976 def list_by_workspace_next_async(next_page_link, custom_headers:nil) fail ArgumentError, 'next_page_link is nil' if next_page_link.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = '{nextLink}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], skip_encoding_path_params: {'nextLink' => next_page_link}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:get, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::PaginatedComputeResourcesList.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Gets computes in specified workspace.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 962 def list_by_workspace_next_with_http_info(next_page_link, custom_headers:nil) list_by_workspace_next_async(next_page_link, custom_headers:custom_headers).value! end
Gets computes in specified workspace.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param skiptoken [String] Continuation token for pagination. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 54 def list_by_workspace_with_http_info(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) list_by_workspace_async(resource_group_name, workspace_name, skiptoken:skiptoken, custom_headers:custom_headers).value! end
Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeSecrets] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 497 def list_keys(resource_group_name, workspace_name, compute_name, custom_headers:nil) response = list_keys_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! response.body unless response.nil? end
Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 532 def list_keys_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listKeys' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeSecrets.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Gets secrets related to Machine Learning compute (storage keys, service credentials, etc).
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 515 def list_keys_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) list_keys_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Array<AmlComputeNodeInformation>] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 393 def list_nodes(resource_group_name, workspace_name, compute_name, custom_headers:nil) first_page = list_nodes_as_lazy(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers) first_page.get_all_items end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [AmlComputeNodesInformation] which provide lazy access to pages of the response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1158 def list_nodes_as_lazy(resource_group_name, workspace_name, compute_name, custom_headers:nil) response = list_nodes_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! unless response.nil? page = response.body page.next_method = Proc.new do |next_page_link| list_nodes_next_async(next_page_link, custom_headers:custom_headers) end page end end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 428 def list_nodes_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) fail ArgumentError, '@client.subscription_id is nil' if @client.subscription_id.nil? fail ArgumentError, 'resource_group_name is nil' if resource_group_name.nil? fail ArgumentError, 'workspace_name is nil' if workspace_name.nil? fail ArgumentError, 'compute_name is nil' if compute_name.nil? fail ArgumentError, '@client.api_version is nil' if @client.api_version.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = 'subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/computes/{computeName}/listNodes' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], path_params: {'subscriptionId' => @client.subscription_id,'resourceGroupName' => resource_group_name,'workspaceName' => workspace_name,'computeName' => compute_name}, query_params: {'api-version' => @client.api_version}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::AmlComputeNodesInformation.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [AmlComputeNodesInformation] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1038 def list_nodes_next(next_page_link, custom_headers:nil) response = list_nodes_next_async(next_page_link, custom_headers:custom_headers).value! response.body unless response.nil? end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] Promise object which holds the HTTP response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1069 def list_nodes_next_async(next_page_link, custom_headers:nil) fail ArgumentError, 'next_page_link is nil' if next_page_link.nil? request_headers = {} request_headers['Content-Type'] = 'application/json; charset=utf-8' # Set Headers request_headers['x-ms-client-request-id'] = SecureRandom.uuid request_headers['accept-language'] = @client.accept_language unless @client.accept_language.nil? path_template = '{nextLink}' request_url = @base_url || @client.base_url options = { middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]], skip_encoding_path_params: {'nextLink' => next_page_link}, headers: request_headers.merge(custom_headers || {}), base_url: request_url } promise = @client.make_request_async(:post, path_template, options) promise = promise.then do |result| http_response = result.response status_code = http_response.status response_content = http_response.body unless status_code == 200 error_model = JSON.load(response_content) fail MsRest::HttpOperationError.new(result.request, http_response, error_model) end result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil? result.correlation_request_id = http_response['x-ms-correlation-request-id'] unless http_response['x-ms-correlation-request-id'].nil? result.client_request_id = http_response['x-ms-client-request-id'] unless http_response['x-ms-client-request-id'].nil? # Deserialize Response if status_code == 200 begin parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content) result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::AmlComputeNodesInformation.mapper() result.body = @client.deserialize(result_mapper, parsed_response) rescue Exception => e fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result) end end result end promise.execute end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param next_page_link [String] The NextLink from the previous successful call to List operation. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1054 def list_nodes_next_with_http_info(next_page_link, custom_headers:nil) list_nodes_next_async(next_page_link, custom_headers:custom_headers).value! end
Get the details (e.g IP address, port etc) of all the compute nodes in the compute.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [MsRestAzure::AzureOperationResponse] HTTP response information.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 411 def list_nodes_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) list_nodes_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value! end
Updates properties of a compute. This call will overwrite a compute if it exists. This is a nonrecoverable operation.
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ClusterUpdateParameters] Additional parameters for cluster update. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [ComputeResource] operation results.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 296 def update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) response = update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers).value! response.body unless response.nil? end
@param resource_group_name [String] Name of the resource group in which workspace is located. @param workspace_name [String] Name of Azure
Machine Learning workspace. @param compute_name [String] Name of the Azure
Machine Learning compute. @param parameters [ClusterUpdateParameters] Additional parameters for cluster update. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.
@return [Concurrent::Promise] promise which provides async access to http response.
# File lib/2018-11-19/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 314 def update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) # Send request promise = begin_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:custom_headers) promise = promise.then do |response| # Defining deserialization method. deserialize_method = lambda do |parsed_response| result_mapper = Azure::MachineLearningServices::Mgmt::V2018_11_19::Models::ComputeResource.mapper() parsed_response = @client.deserialize(result_mapper, parsed_response) end # Waiting for response. @client.get_long_running_operation_result(response, deserialize_method) end promise end