"AIFunctions" ERROR

[user1462]

Hi everyone,

I am trying to build a Machine Learning model in Power BI following this tutorial: 
Tutorial: Build a Machine Learning model in Power BI 

I followed exactly the same steps, however now in the end, I cannot refresh my dataflow and this is the error I got:

I really don't know what does it suppose to mean, could you please help me with it?

Thank you very much in advance!

Here is the mashup script if you're interested:

---------- Message ----------
DataSource.Error: An error happened while reading data from the provider: 'Could not find a transform with the specified Key 'AutoML.Online Shoppers Intent.Purchase Intent Prediction_Revenue''

---------- Session ID ----------
71f80d70-2875-4c7c-a94d-f4634e59729a

---------- Request ID ----------
38f16f07-6029-45f5-9c60-d6a950328f98

---------- Mashup script ----------
section Section1;
shared #"Online Visitors" = let
Source = Csv.Document(Web.Contents("https://raw.githubusercontent.com/santoshc1/PowerBI-AI-samples/master/Tutorial_AutomatedML/online_shoppers_intention.csv"), [Delimiter = ",", Columns = 18, QuoteStyle = QuoteStyle.None]),
#"Promoted headers" = Table.PromoteHeaders(Source, [PromoteAllScalars = true]),
#"Changed column type" = Table.TransformColumnTypes(#"Promoted headers", {{"Administrative", Int64.Type}, {"Administrative_Duration", type number}, {"Informational", Int64.Type}, {"Informational_Duration", type number}, {"ProductRelated", Int64.Type}, {"ProductRelated_Duration", type number}, {"BounceRates", type number}, {"ExitRates", type number}, {"PageValues", type number}, {"SpecialDay", type number}, {"Month", type text}, {"OperatingSystems", Int64.Type}, {"Browser", Int64.Type}, {"Region", Int64.Type}, {"TrafficType", Int64.Type}, {"VisitorType", type text}, {"Weekend", type logical}, {"Revenue", type text}}),
#"Invoked Online Shoppers Intent.Purchase Intent Prediction_Revenue" = Table.AddColumn(#"Changed column type", "Online Shoppers Intent.Purchase Intent Prediction_Revenue", each #"Online Shoppers Intent.Purchase Intent Prediction_Revenue"([Administrative], [Administrative_Duration], [Informational], [Informational_Duration], [ProductRelated], [ProductRelated_Duration], [BounceRates], [ExitRates], [PageValues], [SpecialDay], [Month], [OperatingSystems], [Region], [TrafficType], [Weekend])),
#"Post process Online Shoppers Intent.Purchase Intent Prediction_Revenue" = AIFunctions.PostProcess(#"Invoked Online Shoppers Intent.Purchase Intent Prediction_Revenue", "Online Shoppers Intent.Purchase Intent Prediction_Revenue", Record.FieldOrDefault(Value.Metadata(#"Online Shoppers Intent.Purchase Intent Prediction_Revenue"), "PostProcessFunctionName", "AutoML.Online Shoppers Intent.Purchase Intent Prediction_Revenue"))
in
#"Post process Online Shoppers Intent.Purchase Intent Prediction_Revenue";
shared #"Purchase Intent Prediction Training Data" = let
Source = #"Online Visitors",
#"Selected columns" = Table.SelectColumns(Source, {"Administrative", "Administrative_Duration", "Informational", "Informational_Duration", "ProductRelated", "ProductRelated_Duration", "BounceRates", "ExitRates", "PageValues", "SpecialDay", "Month", "OperatingSystems", "Region", "TrafficType", "Weekend", "Revenue"}),
#"Removed nulls" = Table.SelectRows(#"Selected columns", each [Revenue] <> null and [Revenue] <> ""),
#"Add conditional column" = Table.AddColumn(#"Removed nulls", "TRUE", each if [Revenue] = "TRUE" then true else false),
#"Changed Type" = Table.TransformColumnTypes(#"Add conditional column", {{"TRUE", type logical}}),
#"Remove column" = Table.RemoveColumns(#"Changed Type", {"Revenue"}),
#"Sampled input Wrapper" = (table) => AI.SampleStratifiedWithHoldout("TRUE", Table.RowCount(table), table),
#"Sampled input" = #"Sampled input Wrapper"(#"Remove column")
in
#"Sampled input";
shared #"Purchase Intent Prediction" = let
Source = #"Purchase Intent Prediction Training Data",
DataflowPrecalculatedSource = PowerBI.Dataflows(),
Workspace = DataflowPrecalculatedSource{[workspaceId = "f5e3b32e-67bf-475b-84bd-0f76617df3b1"]}[Data],
Dataflow = Workspace{[dataflowId = "bd85ae0e-67ee-4a7f-aec8-971194f2951a"]}[Data],
Preview = Dataflow{[entity = "Purchase Intent Prediction"]}[Data],
#"Invoked TrainPrediction Wrapper" = (arguments) => AIFunctions.Contents(){[Key = "AI.Execute"]}[Data]("AI.TrainPredictionWithTimeout", "Regular", arguments),
#"Invoked TrainPrediction" = #"Invoked TrainPrediction Wrapper"([labelColumnName = "TRUE", data = Source, timeout = 30]),
#"Selected training schema columns" = Table.Buffer(Table.SelectColumns(#"Invoked TrainPrediction", {"TrainingId", "Model", "Stats", "GlobalExplanation", "TrainingSchema", "TrainingAUC", "LabelColumn"})),
ModelEntity = if (Table.First(#"Selected training schema columns")[Model]="Unavailable") = true then #"Preview" else #"Selected training schema columns"
in
ModelEntity;
shared #"Purchase Intent Prediction.Score" = let
ApplyScoringFunction = (inputQuery as table, newColumn as text, decisionThreshold as number) => let
MlModel = #"Purchase Intent Prediction",
MlModelJson = try Text.FromBinary(Json.FromValue(MlModel{0})) otherwise "InvalidModel",
IsDefaultResponse = if MlModelJson = "InvalidModel" then true else false,
Source = inputQuery,
SelectedBaseEntityColumns = {"Administrative", "Administrative_Duration", "Informational", "Informational_Duration", "ProductRelated", "ProductRelated_Duration", "BounceRates", "ExitRates", "PageValues", "SpecialDay", "Month", "OperatingSystems", "Region", "TrafficType", "Weekend"},
InputRowCount = Table.RowCount(Source),
InputTableType = Value.Type(Source),
SelectedColumnsTypes = List.Transform(SelectedBaseEntityColumns, each Type.TableColumn(InputTableType, _)),
DefaultRecord = Record.FromList({0,"Unavailable"}, type[PredictionScore = text,PredictionExplanation = text]),
DefaultTable = Table.FromRecords({DefaultRecord}),
ExpandedDefaultTable = Table.Repeat(DefaultTable, InputRowCount),
ScoringFunction = 
let
ScoringFunctionScalarType = type function (row as record) as any,
VectorizedScoringFunction = (input as table) =>
let
ExpandedColumns = Table.ExpandRecordColumn(input, "row", SelectedBaseEntityColumns),
ExpandedColumnsWithTypes = Table.TransformColumnTypes(ExpandedColumns, List.Zip({SelectedBaseEntityColumns, SelectedColumnsTypes})),
ErrorList = List.Repeat({[Output = null]}, InputRowCount),
Result = if MlModelJson <> "InvalidModel" then (try Table.ToRecords(AIFunctions.Contents(){[Key = "AI.Execute"]}[Data]("AI.ScorePrediction", "Vectorized", [data = ExpandedColumns, scoreParameters = MlModelJson])) otherwise ErrorList) else ErrorList
in
Result,
ScalarVectorScoringFunction = Function.ScalarVector(ScoringFunctionScalarType, VectorizedScoringFunction)
in
ScalarVectorScoringFunction,
CombinedTablesDefault = Table.NestedJoin(Source, {}, ExpandedDefaultTable, {}, newColumn, JoinKind.FullOuter),
CombinedTablesAI = Table.AddColumn(Source, newColumn, each ScoringFunction(_)),
AddScoringColumn = if IsDefaultResponse = true then CombinedTablesDefault else CombinedTablesAI,
ExpandResultColumns = if IsDefaultResponse = true then Table.ExpandTableColumn(AddScoringColumn, newColumn, {"PredictionScore", "PredictionExplanation"}, {Text.Combine({newColumn, "PredictionScore"}, "."), Text.Combine({newColumn, "PredictionExplanation"}, ".")}) else Table.ExpandRecordColumn(AddScoringColumn, newColumn, {"PredictionScore", "PredictionExplanation"}, {Text.Combine({newColumn, "PredictionScore"}, "."), Text.Combine({newColumn, "PredictionExplanation"}, ".")}),
LabeledOutput = Table.AddColumn(ExpandResultColumns, Text.Combine({newColumn, "Outcome"}, "."), each Record.Field(_, Text.Combine({newColumn, "PredictionScore"}, ".")) >= decisionThreshold * 100),
ReplacedErrors = Table.ReplaceErrorValues(LabeledOutput, {{Text.Combine({newColumn, "Outcome"}, "."), null}, {Text.Combine({newColumn, "PredictionScore"}, "."), null}, {Text.Combine({newColumn, "PredictionExplanation"}, "."), null}}),
TransformTypes = Table.TransformColumnTypes(ReplacedErrors, {{Text.Combine({newColumn, "Outcome"}, "."), type logical}, {Text.Combine({newColumn, "PredictionScore"}, "."), type text}, {Text.Combine({newColumn, "PredictionExplanation"}, "."), type text}})
in
TransformTypes
in
ApplyScoringFunction;
shared #"Purchase Intent Prediction_PollingQuery" = let
Source = "9979dc32-8de8-481c-bdc6-df63deeb945b"
in
Source;
shared #"Purchase Intent Prediction Testing Data" = let
Source = #"Purchase Intent Prediction Training Data",
DataflowPrecalculatedSource = PowerBI.Dataflows(),
Workspace = DataflowPrecalculatedSource{[workspaceId = "f5e3b32e-67bf-475b-84bd-0f76617df3b1"]}[Data],
Dataflow = Workspace{[dataflowId = "bd85ae0e-67ee-4a7f-aec8-971194f2951a"]}[Data],
TestingPreview = Dataflow{[entity = "Purchase Intent Prediction Testing Data"]}[Data],
#"Filtered rows" = Table.SelectRows(Source, each ([__IsTraining__] = false)),
AddExplanationsIndex = Table.AddIndexColumn(#"Filtered rows", Text.Combine({"Purchase Intent PredictionOutput", "ExplanationIndex"}, "."), 1, 1),
#"Invoked Scoring" = #"Purchase Intent Prediction.Score"(AddExplanationsIndex, "Purchase Intent PredictionOutput", 0.5),
#"Test Result" = if (Table.First(#"Invoked Scoring")[#"Purchase Intent PredictionOutput.PredictionExplanation"]="Unavailable") = true then #"TestingPreview" else #"Invoked Scoring"
in
#"Test Result";
shared #"Online Visitors enriched Purchase Intent Prediction" = let
Source = #"Online Visitors",
AddExplanationsIndex = Table.AddIndexColumn(Source, Text.Combine({"Purchase Intent Prediction", "ExplanationIndex"}, "."), 1, 1),
#"Invoked Purchase Intent Prediction.Score" = #"Purchase Intent Prediction.Score"(AddExplanationsIndex, "Purchase Intent Prediction", 0.75),
DataflowPrecalculatedSource = PowerBI.Dataflows(),
Workspace = DataflowPrecalculatedSource{[workspaceId = "f5e3b32e-67bf-475b-84bd-0f76617df3b1"]}[Data],
Dataflow = Workspace{[dataflowId = "bd85ae0e-67ee-4a7f-aec8-971194f2951a"]}[Data],
EnrichedPreview = Dataflow{[entity = "Online Visitors enriched Purchase Intent Prediction"]}[Data],
#"Enriched results" = if (Table.First(#"Invoked Purchase Intent Prediction.Score")[#"Purchase Intent Prediction.PredictionExplanation"]="Unavailable") = true then #"EnrichedPreview" else #"Invoked Purchase Intent Prediction.Score"
in
#"Enriched results";
shared #"Online Visitors enriched Purchase Intent Prediction explanations" = let
Source = #"Online Visitors enriched Purchase Intent Prediction",
OutputColumnName = "Purchase Intent Prediction.",
SelectExplanationColumns = Table.SelectColumns(Source, {Text.Combine({OutputColumnName, "Outcome"}), Text.Combine({OutputColumnName, "PredictionExplanation"}), Text.Combine({OutputColumnName, "ExplanationIndex"})}, MissingField.UseNull),
ParseCsv = Table.TransformColumns(SelectExplanationColumns, {Text.Combine({OutputColumnName, "PredictionExplanation"}), each try Csv.Document(_, {"Field", "Type", "Contribution", "Value", "ExplanationsDisplayText"}, ",") otherwise null}, null, MissingField.UseNull),
ExpandCsv = Table.ExpandTableColumn(ParseCsv, Text.Combine({OutputColumnName, "PredictionExplanation"}), {"Field", "Type", "Contribution", "Value", "ExplanationsDisplayText"}, {"Field", "Type", "Contribution", "Value", "ExplanationsDisplayText"}),
ChangeTypes = Table.TransformColumnTypes(ExpandCsv, {{"Field", type text}, {"Type", type text}, {"Contribution", type text}, {"Value", type text}, {"ExplanationsDisplayText", type text}}),
RemoveErrors = Table.RemoveRowsWithErrors(ChangeTypes, {"Field", "Type", "Contribution", "Value", "ExplanationsDisplayText"}),
RemoveBlank = Table.SelectRows(RemoveErrors, each not List.IsEmpty(List.RemoveMatchingItems(Record.FieldValues(Record.SelectFields(_, {"Field", "Type", "Contribution", "Value", "ExplanationsDisplayText"})), {"", null})))
in
RemoveBlank;
shared #"Online Shoppers Intent.Purchase Intent Prediction_Revenue" = AIFunctions.Contents(){[Key = "AutoML.Online Shoppers Intent.Purchase Intent Prediction_Revenue"]}[Data];

[v-xinruzhu-msft]

Hi @user1462 

Did you make some change on your data source?it seems that your data source has some mistakes, maybe you can the key i marked in the picture

^{Best Regards,}

^{Yolo Zhu}

^{If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.}

[user1462]

No actually I didn't make any changes, it was correctly working until the last step of the tutorial, and lastly when I invoke the AutoML models on the workspace and save it, it gives me this error while refreshing the dataflow.