class Azure::MachineLearningServices::Mgmt::V2019_05_01::MachineLearningCompute

These APIs allow end users to operate on Azure Machine Learning Workspace resources.

Attributes

client[R]

@return [MachineLearningServicesClient] reference to the MachineLearningServicesClient

Private Class Methods

new(client) click to toggle source

Creates and initializes a new instance of the MachineLearningCompute class. @param client service class for accessing basic functionality.

# File lib/2019-05-01/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 18
def initialize(client)
  @client = client
end

Private Instance Methods

begin_create_or_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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::V2019_05_01::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::V2019_05_01::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
begin_create_or_update_with_http_info(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_delete(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_delete_with_http_info(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
begin_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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::V2019_05_01::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
begin_update_with_http_info(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
create_or_update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
create_or_update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

@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/2019-05-01/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::V2019_05_01::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
delete(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) click to toggle source

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/2019-05-01/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
delete_async(resource_group_name, workspace_name, compute_name, underlying_resource_action, custom_headers:nil) click to toggle source

@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/2019-05-01/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
get(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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
get_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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
get_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_by_workspace(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_by_workspace_as_lazy(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) click to toggle source

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/2019-05-01/generated/azure_mgmt_machine_learning_services/machine_learning_compute.rb, line 1040
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
list_by_workspace_async(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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
list_by_workspace_next(next_page_link, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_by_workspace_next_async(next_page_link, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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
list_by_workspace_next_with_http_info(next_page_link, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_by_workspace_with_http_info(resource_group_name, workspace_name, skiptoken:nil, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_keys(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_keys_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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
list_keys_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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
list_nodes(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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] operation results.

# File lib/2019-05-01/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)
  response = list_nodes_async(resource_group_name, workspace_name, compute_name, custom_headers:custom_headers).value!
  response.body unless response.nil?
end
list_nodes_async(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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::V2019_05_01::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
list_nodes_with_http_info(resource_group_name, workspace_name, compute_name, custom_headers:nil) click to toggle source

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/2019-05-01/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
update(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

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/2019-05-01/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
update_async(resource_group_name, workspace_name, compute_name, parameters, custom_headers:nil) click to toggle source

@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/2019-05-01/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::V2019_05_01::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