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;
}
}