/// <summary>
/// Initiates the asynchronous execution of the DescribeEvaluations operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DescribeEvaluations 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<DescribeEvaluationsResponse> DescribeEvaluationsAsync(DescribeEvaluationsRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var marshaller = new DescribeEvaluationsRequestMarshaller();
var unmarshaller = DescribeEvaluationsResponseUnmarshaller.Instance;
return InvokeAsync<DescribeEvaluationsRequest,DescribeEvaluationsResponse>(request, marshaller,
unmarshaller, cancellationToken);
}
private Amazon.MachineLearning.Model.DescribeEvaluationsResponse CallAWSServiceOperation(IAmazonMachineLearning client, Amazon.MachineLearning.Model.DescribeEvaluationsRequest request)
{
Utils.Common.WriteVerboseEndpointMessage(this, client.Config, "Amazon Machine Learning", "DescribeEvaluations");
try
{
#if DESKTOP
return(client.DescribeEvaluations(request));
#elif CORECLR
return(client.DescribeEvaluationsAsync(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 DescribeEvaluationsResponse DescribeEvaluations(DescribeEvaluationsRequest request)
{
var marshaller = new DescribeEvaluationsRequestMarshaller();
var unmarshaller = DescribeEvaluationsResponseUnmarshaller.Instance;
return Invoke<DescribeEvaluationsRequest,DescribeEvaluationsResponse>(request, marshaller, unmarshaller);
}
public object Execute(ExecutorContext context)
{
var cmdletContext = context as CmdletContext;
var useParameterSelect = this.Select.StartsWith("^");
// create request and set iteration invariants
var request = new Amazon.MachineLearning.Model.DescribeEvaluationsRequest();
if (cmdletContext.EQ != null)
{
request.EQ = cmdletContext.EQ;
}
if (cmdletContext.FilterVariable != null)
{
request.FilterVariable = cmdletContext.FilterVariable;
}
if (cmdletContext.GE != null)
{
request.GE = cmdletContext.GE;
}
if (cmdletContext.GT != null)
{
request.GT = cmdletContext.GT;
}
if (cmdletContext.LE != null)
{
request.LE = cmdletContext.LE;
}
if (cmdletContext.LT != null)
{
request.LT = cmdletContext.LT;
}
if (cmdletContext.NE != null)
{
request.NE = cmdletContext.NE;
}
if (cmdletContext.Prefix != null)
{
request.Prefix = cmdletContext.Prefix;
}
if (cmdletContext.SortOrder != null)
{
request.SortOrder = cmdletContext.SortOrder;
}
// Initialize loop variants and commence piping
System.String _nextToken = null;
int? _emitLimit = null;
int _retrievedSoFar = 0;
if (AutoIterationHelpers.HasValue(cmdletContext.NextToken))
{
_nextToken = cmdletContext.NextToken;
}
if (AutoIterationHelpers.HasValue(cmdletContext.Limit))
{
// The service has a maximum page size of 100. If the user has
// asked for more items than page max, and there is no page size
// configured, we rely on the service ignoring the set maximum
// and giving us 100 items back. If a page size is set, that will
// be used to configure the pagination.
// We'll make further calls to satisfy the user's request.
_emitLimit = cmdletContext.Limit;
}
var _userControllingPaging = this.NoAutoIteration.IsPresent || ParameterWasBound(nameof(this.NextToken));
var client = Client ?? CreateClient(_CurrentCredentials, _RegionEndpoint);
do
{
request.NextToken = _nextToken;
if (_emitLimit.HasValue)
{
int correctPageSize = AutoIterationHelpers.Min(100, _emitLimit.Value);
request.Limit = AutoIterationHelpers.ConvertEmitLimitToInt32(correctPageSize);
}
else
{
request.Limit = AutoIterationHelpers.ConvertEmitLimitToInt32(100);
}
CmdletOutput output;
try
{
var response = CallAWSServiceOperation(client, request);
object pipelineOutput = null;
if (!useParameterSelect)
{
pipelineOutput = cmdletContext.Select(response, this);
}
output = new CmdletOutput
{
PipelineOutput = pipelineOutput,
ServiceResponse = response
};
int _receivedThisCall = response.Results.Count;
_nextToken = response.NextToken;
_retrievedSoFar += _receivedThisCall;
if (_emitLimit.HasValue)
{
_emitLimit -= _receivedThisCall;
}
}
catch (Exception e)
{
if (_retrievedSoFar == 0 || !_emitLimit.HasValue)
{
output = new CmdletOutput {
ErrorResponse = e
};
}
else
{
break;
}
}
ProcessOutput(output);
} while (!_userControllingPaging && AutoIterationHelpers.HasValue(_nextToken) && (!_emitLimit.HasValue || _emitLimit.Value >= 1));
if (useParameterSelect)
{
WriteObject(cmdletContext.Select(null, this));
}
return(null);
}
public object Execute(ExecutorContext context)
{
var cmdletContext = context as CmdletContext;
var useParameterSelect = this.Select.StartsWith("^");
// create request and set iteration invariants
var request = new Amazon.MachineLearning.Model.DescribeEvaluationsRequest();
if (cmdletContext.EQ != null)
{
request.EQ = cmdletContext.EQ;
}
if (cmdletContext.FilterVariable != null)
{
request.FilterVariable = cmdletContext.FilterVariable;
}
if (cmdletContext.GE != null)
{
request.GE = cmdletContext.GE;
}
if (cmdletContext.GT != null)
{
request.GT = cmdletContext.GT;
}
if (cmdletContext.LE != null)
{
request.LE = cmdletContext.LE;
}
if (cmdletContext.Limit != null)
{
request.Limit = AutoIterationHelpers.ConvertEmitLimitToServiceTypeInt32(cmdletContext.Limit.Value);
}
if (cmdletContext.LT != null)
{
request.LT = cmdletContext.LT;
}
if (cmdletContext.NE != null)
{
request.NE = cmdletContext.NE;
}
if (cmdletContext.Prefix != null)
{
request.Prefix = cmdletContext.Prefix;
}
if (cmdletContext.SortOrder != null)
{
request.SortOrder = cmdletContext.SortOrder;
}
// Initialize loop variant and commence piping
var _nextToken = cmdletContext.NextToken;
var _userControllingPaging = this.NoAutoIteration.IsPresent || ParameterWasBound(nameof(this.NextToken));
var client = Client ?? CreateClient(_CurrentCredentials, _RegionEndpoint);
do
{
request.NextToken = _nextToken;
CmdletOutput output;
try
{
var response = CallAWSServiceOperation(client, request);
object pipelineOutput = null;
if (!useParameterSelect)
{
pipelineOutput = cmdletContext.Select(response, this);
}
output = new CmdletOutput
{
PipelineOutput = pipelineOutput,
ServiceResponse = response
};
_nextToken = response.NextToken;
}
catch (Exception e)
{
output = new CmdletOutput {
ErrorResponse = e
};
}
ProcessOutput(output);
} while (!_userControllingPaging && AutoIterationHelpers.HasValue(_nextToken));
if (useParameterSelect)
{
WriteObject(cmdletContext.Select(null, this));
}
return(null);
}
/// <summary>
/// Paginator for DescribeEvaluations operation
///</summary>
public IDescribeEvaluationsPaginator DescribeEvaluations(DescribeEvaluationsRequest request)
{
return(new DescribeEvaluationsPaginator(this.client, request));
}
/// <summary>
/// Initiates the asynchronous execution of the DescribeEvaluations operation.
/// </summary>
///
/// <param name="request">Container for the necessary parameters to execute the DescribeEvaluations 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 EndDescribeEvaluations
/// operation.</returns>
public IAsyncResult BeginDescribeEvaluations(DescribeEvaluationsRequest request, AsyncCallback callback, object state)
{
var marshaller = new DescribeEvaluationsRequestMarshaller();
var unmarshaller = DescribeEvaluationsResponseUnmarshaller.Instance;
return BeginInvoke<DescribeEvaluationsRequest>(request, marshaller, unmarshaller,
callback, state);
}
internal DescribeEvaluationsPaginator(IAmazonMachineLearning client, DescribeEvaluationsRequest request)
{
this._client = client;
this._request = request;
}