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);
}
