public object Execute(ExecutorContext context) { var cmdletContext = context as CmdletContext; // create request var request = new Amazon.MachineLearning.Model.GetEvaluationRequest(); if (cmdletContext.EvaluationId != null) { request.EvaluationId = cmdletContext.EvaluationId; } 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 GetEvaluation operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the GetEvaluation 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<GetEvaluationResponse> GetEvaluationAsync(GetEvaluationRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken)) { var marshaller = new GetEvaluationRequestMarshaller(); var unmarshaller = GetEvaluationResponseUnmarshaller.Instance; return InvokeAsync<GetEvaluationRequest,GetEvaluationResponse>(request, marshaller, unmarshaller, cancellationToken); }
/// <summary> /// Returns an <code>Evaluation</code> that includes metadata as well as the current status /// of the <code>Evaluation</code>. /// </summary> /// <param name="evaluationId">The ID of the <code>Evaluation</code> to retrieve. The evaluation of each <code>MLModel</code> is recorded and cataloged. The ID provides the means to access the information. </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 GetEvaluation 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<GetEvaluationResponse> GetEvaluationAsync(string evaluationId, System.Threading.CancellationToken cancellationToken = default(CancellationToken)) { var request = new GetEvaluationRequest(); request.EvaluationId = evaluationId; return GetEvaluationAsync(request, cancellationToken); }
internal GetEvaluationResponse GetEvaluation(GetEvaluationRequest request) { var marshaller = new GetEvaluationRequestMarshaller(); var unmarshaller = GetEvaluationResponseUnmarshaller.Instance; return Invoke<GetEvaluationRequest,GetEvaluationResponse>(request, marshaller, unmarshaller); }
/// <summary> /// Returns an <code>Evaluation</code> that includes metadata as well as the current status /// of the <code>Evaluation</code>. /// </summary> /// <param name="evaluationId">The ID of the <code>Evaluation</code> to retrieve. The evaluation of each <code>MLModel</code> is recorded and cataloged. The ID provides the means to access the information. </param> /// /// <returns>The response from the GetEvaluation 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 GetEvaluationResponse GetEvaluation(string evaluationId) { var request = new GetEvaluationRequest(); request.EvaluationId = evaluationId; return GetEvaluation(request); }
/// <summary> /// Initiates the asynchronous execution of the GetEvaluation operation. /// </summary> /// /// <param name="request">Container for the necessary parameters to execute the GetEvaluation 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 EndGetEvaluation /// operation.</returns> public IAsyncResult BeginGetEvaluation(GetEvaluationRequest request, AsyncCallback callback, object state) { var marshaller = new GetEvaluationRequestMarshaller(); var unmarshaller = GetEvaluationResponseUnmarshaller.Instance; return BeginInvoke<GetEvaluationRequest>(request, marshaller, unmarshaller, callback, state); }
private Amazon.MachineLearning.Model.GetEvaluationResponse CallAWSServiceOperation(IAmazonMachineLearning client, Amazon.MachineLearning.Model.GetEvaluationRequest request) { Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Machine Learning", "GetEvaluation"); try { #if DESKTOP return(client.GetEvaluation(request)); #elif CORECLR return(client.GetEvaluationAsync(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; } }