diff --git a/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs b/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs
index b92ee04909..1537ab10cf 100644
--- a/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs
+++ b/src/Microsoft.ML.TensorFlow/TensorflowTransform.cs
@@ -110,8 +110,9 @@ internal TensorFlowTransformer(IHostEnvironment env, TensorFlowModel tfModelInfo
/// The output columns to generate. Names must match model specifications. Data types are inferred from model.
/// Add a batch dimension to the input e.g. input = [224, 224, 3] => [-1, 224, 224, 3].
/// This parameter is used to deal with models that have unknown shape but the internal operators in the model require data to have batch dimension as well.
- internal TensorFlowTransformer(IHostEnvironment env, TensorFlowModel tfModelInfo, string[] outputColumnNames, string[] inputColumnNames, bool addBatchDimensionInput = false)
- : this(env, tfModelInfo.Session, outputColumnNames, inputColumnNames, IsSavedModel(env, tfModelInfo.ModelPath) ? tfModelInfo.ModelPath : null, false, addBatchDimensionInput)
+ /// If the first dimension of the output is unknown, should it be treated as batched or not.
+ internal TensorFlowTransformer(IHostEnvironment env, TensorFlowModel tfModelInfo, string[] outputColumnNames, string[] inputColumnNames, bool addBatchDimensionInput = false, bool treatOutputAsBatched = true)
+ : this(env, tfModelInfo.Session, outputColumnNames, inputColumnNames, IsSavedModel(env, tfModelInfo.ModelPath) ? tfModelInfo.ModelPath : null, false, addBatchDimensionInput, treatOutputAsBatched: treatOutputAsBatched)
{
}
@@ -898,9 +899,9 @@ internal sealed class Options : TransformInputBase
/// If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unknown length when this is false.
///
///
- /// This parameter is used to deal with models that have unknown output shape and it needs to be interpreted in ML.NET as a vector of unkown length and not as a batch dimension.
+ /// This parameter is used to deal with models that have unknown output shape and it needs to be interpreted in ML.NET as a vector of unknown length and not as a batch dimension.
///
- [Argument(ArgumentType.AtMostOnce, HelpText = "If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unkown length when this is false.", SortOrder = 17)]
+ [Argument(ArgumentType.AtMostOnce, HelpText = "If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unknown length when this is false.", SortOrder = 17)]
public bool TreatOutputAsBatched = true;
}
diff --git a/src/Microsoft.ML.TensorFlow/TensorflowUtils.cs b/src/Microsoft.ML.TensorFlow/TensorflowUtils.cs
index 39141d77d2..8fbbd772a0 100644
--- a/src/Microsoft.ML.TensorFlow/TensorflowUtils.cs
+++ b/src/Microsoft.ML.TensorFlow/TensorflowUtils.cs
@@ -99,9 +99,9 @@ internal static DataViewSchema GetModelSchema(IExceptionContext ectx, Graph grap
columnType = new VectorDataViewType(mlType, tensorShape[0] > 0 ? tensorShape : tensorShape.Skip(1).ToArray());
}
// When treatOutputAsBatched is false, if the first value is less than 0 we want to set it to 0. TensorFlow
- // represents an unkown size as -1, but ML.NET represents it as 0 so we need to convert it.
- // I.E. if the input dimensions are [-1, 5], ML.NET will read the -1 as a dimension of unkown length, and so the ML.NET
- // data type will be a vector of 2 dimensions, where the first dimension is unkown and the second has a length of 5.
+ // represents an unknown size as -1, but ML.NET represents it as 0 so we need to convert it.
+ // I.E. if the input dimensions are [-1, 5], ML.NET will read the -1 as a dimension of unknown length, and so the ML.NET
+ // data type will be a vector of 2 dimensions, where the first dimension is unknown and the second has a length of 5.
else
{
if (tensorShape[0] < 0)
diff --git a/test/BaselineOutput/Common/EntryPoints/core_manifest.json b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
index b3445a4149..7253e4533f 100644
--- a/test/BaselineOutput/Common/EntryPoints/core_manifest.json
+++ b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
@@ -23617,7 +23617,7 @@
{
"Name": "TreatOutputAsBatched",
"Type": "Bool",
- "Desc": "If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unkown length when this is false.",
+ "Desc": "If the first dimension of the output is unknown, should it be treated as batched or not. e.g. output = [-1] will be read as a vector of unknown length when this is false.",
"Required": false,
"SortOrder": 17.0,
"IsNullable": false,
diff --git a/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs b/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs
index 6d1ab87e5d..ff6dbd456f 100644
--- a/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs
+++ b/test/Microsoft.ML.Tests/TensorFlowEstimatorTests.cs
@@ -183,7 +183,7 @@ public void TestTensorFlow()
Assert.Equal(4, numRows);
}
}
-
+
[TensorFlowFact]
public void TreatOutputAsBatched()
{
@@ -211,7 +211,7 @@ public void TreatOutputAsBatched()
var schema = pipe.Fit(data).Transform(data).Schema;
// The dimensions of the output with treatOutputAsBatched set to false should be * 10
- // as the first dimension of -1 is treated as an unkown dimension.
+ // as the first dimension of -1 is treated as an unknown dimension.
Assert.Equal(new VectorDataViewType(NumberDataViewType.Single, 0, 10), schema["Output"].Type);
// Note that CamelCase column names are there to match the TF graph node names.