public object Execute(ExecutorContext context) { var cmdletContext = context as CmdletContext; // create request var request = new Amazon.MachineLearning.Model.CreateRealtimeEndpointRequest(); if (cmdletContext.MLModelId != null) { request.MLModelId = cmdletContext.MLModelId; } CmdletOutput output; // issue call var client = Client ?? CreateClient(_CurrentCredentials, _RegionEndpoint); try { var response = CallAWSServiceOperation(client, request); object pipelineOutput = null; pipelineOutput = cmdletContext.Select(response, this); output = new CmdletOutput { PipelineOutput = pipelineOutput, ServiceResponse = response }; } catch (Exception e) { output = new CmdletOutput { ErrorResponse = e }; } return(output); }
/// <summary> /// Initiates the asynchronous execution of the CreateRealtimeEndpoint operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the CreateRealtimeEndpoint operation.</param> /// <param name="cancellationToken"> /// A cancellation token that can be used by other objects or threads to receive notice of cancellation. /// </param> /// <returns>The task object representing the asynchronous operation.</returns> public Task<CreateRealtimeEndpointResponse> CreateRealtimeEndpointAsync(CreateRealtimeEndpointRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken)) { var marshaller = new CreateRealtimeEndpointRequestMarshaller(); var unmarshaller = CreateRealtimeEndpointResponseUnmarshaller.Instance; return InvokeAsync<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResponse>(request, marshaller, unmarshaller, cancellationToken); }
/// <summary> /// Creates a real-time endpoint for the <code>MLModel</code>. The endpoint contains the /// URI of the <code>MLModel</code>; that is, the location to send real-time prediction /// requests for the specified <code>MLModel</code>. /// </summary> /// <param name="mlModelId">The ID assigned to the <code>MLModel</code> during creation.</param> /// <param name="cancellationToken"> /// A cancellation token that can be used by other objects or threads to receive notice of cancellation. /// </param> /// /// <returns>The response from the CreateRealtimeEndpoint service method, as returned by MachineLearning.</returns> /// <exception cref="Amazon.MachineLearning.Model.InternalServerException"> /// An error on the server occurred when trying to process a request. /// </exception> /// <exception cref="Amazon.MachineLearning.Model.InvalidInputException"> /// An error on the client occurred. Typically, the cause is an invalid input value. /// </exception> /// <exception cref="Amazon.MachineLearning.Model.ResourceNotFoundException"> /// A specified resource cannot be located. /// </exception> public Task<CreateRealtimeEndpointResponse> CreateRealtimeEndpointAsync(string mlModelId, System.Threading.CancellationToken cancellationToken = default(CancellationToken)) { var request = new CreateRealtimeEndpointRequest(); request.MLModelId = mlModelId; return CreateRealtimeEndpointAsync(request, cancellationToken); }
internal CreateRealtimeEndpointResponse CreateRealtimeEndpoint(CreateRealtimeEndpointRequest request) { var marshaller = new CreateRealtimeEndpointRequestMarshaller(); var unmarshaller = CreateRealtimeEndpointResponseUnmarshaller.Instance; return Invoke<CreateRealtimeEndpointRequest,CreateRealtimeEndpointResponse>(request, marshaller, unmarshaller); }
/// <summary> /// Creates a real-time endpoint for the <code>MLModel</code>. The endpoint contains the /// URI of the <code>MLModel</code>; that is, the location to send real-time prediction /// requests for the specified <code>MLModel</code>. /// </summary> /// <param name="mlModelId">The ID assigned to the <code>MLModel</code> during creation.</param> /// /// <returns>The response from the CreateRealtimeEndpoint service method, as returned by MachineLearning.</returns> /// <exception cref="Amazon.MachineLearning.Model.InternalServerException"> /// An error on the server occurred when trying to process a request. /// </exception> /// <exception cref="Amazon.MachineLearning.Model.InvalidInputException"> /// An error on the client occurred. Typically, the cause is an invalid input value. /// </exception> /// <exception cref="Amazon.MachineLearning.Model.ResourceNotFoundException"> /// A specified resource cannot be located. /// </exception> public CreateRealtimeEndpointResponse CreateRealtimeEndpoint(string mlModelId) { var request = new CreateRealtimeEndpointRequest(); request.MLModelId = mlModelId; return CreateRealtimeEndpoint(request); }
/// <summary> /// Initiates the asynchronous execution of the CreateRealtimeEndpoint operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the CreateRealtimeEndpoint operation on AmazonMachineLearningClient.</param> /// <param name="callback">An AsyncCallback delegate that is invoked when the operation completes.</param> /// <param name="state">A user-defined state object that is passed to the callback procedure. Retrieve this object from within the callback /// procedure using the AsyncState property.</param> /// /// <returns>An IAsyncResult that can be used to poll or wait for results, or both; this value is also needed when invoking EndCreateRealtimeEndpoint /// operation.</returns> public IAsyncResult BeginCreateRealtimeEndpoint(CreateRealtimeEndpointRequest request, AsyncCallback callback, object state) { var marshaller = new CreateRealtimeEndpointRequestMarshaller(); var unmarshaller = CreateRealtimeEndpointResponseUnmarshaller.Instance; return BeginInvoke<CreateRealtimeEndpointRequest>(request, marshaller, unmarshaller, callback, state); }
private Amazon.MachineLearning.Model.CreateRealtimeEndpointResponse CallAWSServiceOperation(IAmazonMachineLearning client, Amazon.MachineLearning.Model.CreateRealtimeEndpointRequest request) { Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Machine Learning", "CreateRealtimeEndpoint"); try { #if DESKTOP return(client.CreateRealtimeEndpoint(request)); #elif CORECLR return(client.CreateRealtimeEndpointAsync(request).GetAwaiter().GetResult()); #else #error "Unknown build edition" #endif } catch (AmazonServiceException exc) { var webException = exc.InnerException as System.Net.WebException; if (webException != null) { throw new Exception(Utils.Common.FormatNameResolutionFailureMessage(client.Config, webException.Message), webException); } throw; } }