public object Execute(ExecutorContext context) { var cmdletContext = context as CmdletContext; // create request var request = new Amazon.MachineLearning.Model.CreateMLModelRequest(); if (cmdletContext.MLModelId != null) { request.MLModelId = cmdletContext.MLModelId; } if (cmdletContext.MLModelName != null) { request.MLModelName = cmdletContext.MLModelName; } if (cmdletContext.MLModelType != null) { request.MLModelType = cmdletContext.MLModelType; } if (cmdletContext.Parameter != null) { request.Parameters = cmdletContext.Parameter; } if (cmdletContext.Recipe != null) { request.Recipe = cmdletContext.Recipe; } if (cmdletContext.RecipeUri != null) { request.RecipeUri = cmdletContext.RecipeUri; } if (cmdletContext.TrainingDataSourceId != null) { request.TrainingDataSourceId = cmdletContext.TrainingDataSourceId; } 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); }
private Amazon.MachineLearning.Model.CreateMLModelResponse CallAWSServiceOperation(IAmazonMachineLearning client, Amazon.MachineLearning.Model.CreateMLModelRequest request) { Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Machine Learning", "CreateMLModel"); try { #if DESKTOP return(client.CreateMLModel(request)); #elif CORECLR return(client.CreateMLModelAsync(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; } }
internal CreateMLModelResponse CreateMLModel(CreateMLModelRequest request) { var marshaller = new CreateMLModelRequestMarshaller(); var unmarshaller = CreateMLModelResponseUnmarshaller.Instance; return Invoke<CreateMLModelRequest,CreateMLModelResponse>(request, marshaller, unmarshaller); }
/// <summary> /// Initiates the asynchronous execution of the CreateMLModel operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the CreateMLModel 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<CreateMLModelResponse> CreateMLModelAsync(CreateMLModelRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken)) { var marshaller = new CreateMLModelRequestMarshaller(); var unmarshaller = CreateMLModelResponseUnmarshaller.Instance; return InvokeAsync<CreateMLModelRequest,CreateMLModelResponse>(request, marshaller, unmarshaller, cancellationToken); }
/// <summary> /// Initiates the asynchronous execution of the CreateMLModel operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the CreateMLModel 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 EndCreateMLModel /// operation.</returns> public IAsyncResult BeginCreateMLModel(CreateMLModelRequest request, AsyncCallback callback, object state) { var marshaller = new CreateMLModelRequestMarshaller(); var unmarshaller = CreateMLModelResponseUnmarshaller.Instance; return BeginInvoke<CreateMLModelRequest>(request, marshaller, unmarshaller, callback, state); }