Treat TensorFlow output as non-batched.

src/Microsoft.ML.TensorFlow/TensorFlowModel.cs

@@ -18,6 +18,7 @@ public sealed class TensorFlowModel : IDisposable
     {
         internal Session Session { get; }
         internal string ModelPath { get; }
+        internal bool TreatOutputAsBatched { get; }
 
         private readonly IHostEnvironment _env;
 
@@ -27,10 +28,12 @@ public sealed class TensorFlowModel : IDisposable
         /// <param name="env">An <see cref="IHostEnvironment"/> object.</param>
         /// <param name="session">TensorFlow session object.</param>
         /// <param name="modelLocation">Location of the model from where <paramref name="session"/> was loaded.</param>
-        internal TensorFlowModel(IHostEnvironment env, Session session, string modelLocation)
+        /// <param name="treatOutputAsBatched">If the first dimension of the output is unknown, should it be treated as batched or not.</param>
+        internal TensorFlowModel(IHostEnvironment env, Session session, string modelLocation, bool treatOutputAsBatched = true)
         {
             Session = session;
             ModelPath = modelLocation;
+            TreatOutputAsBatched = treatOutputAsBatched;
             _env = env;
             _disposed = false;
         }
@@ -40,7 +43,7 @@ internal TensorFlowModel(IHostEnvironment env, Session session, string modelLoca
         /// </summary>
         public DataViewSchema GetModelSchema()
         {
-            return TensorFlowUtils.GetModelSchema(_env, Session.graph);
+            return TensorFlowUtils.GetModelSchema(_env, Session.graph, TreatOutputAsBatched);
         }
 
         /// <summary>
@@ -49,7 +52,7 @@ public DataViewSchema GetModelSchema()
         /// </summary>
         public DataViewSchema GetInputSchema()
         {
-            return TensorFlowUtils.GetModelSchema(_env, Session.graph, "Placeholder");
+            return TensorFlowUtils.GetModelSchema(_env, Session.graph, TreatOutputAsBatched, "Placeholder");
         }
 
         /// <summary>

src/Microsoft.ML.TensorFlow/TensorflowCatalog.cs

@@ -35,5 +35,31 @@ public static class TensorflowCatalog
         /// </example>
         public static TensorFlowModel LoadTensorFlowModel(this ModelOperationsCatalog catalog, string modelLocation)
             => TensorFlowUtils.LoadTensorFlowModel(CatalogUtils.GetEnvironment(catalog), modelLocation);
+
+        /// <summary>
+        /// Load TensorFlow model into memory. This is the convenience method that allows the model to be loaded once and subsequently use it for querying schema and creation of
+        /// <see cref="TensorFlowEstimator"/> using <see cref="TensorFlowModel.ScoreTensorFlowModel(string, string, bool)"/>.
+        /// usage of this API requires additional NuGet dependencies on TensorFlow redist, see linked document for more information.
+        /// <see cref="TensorFlowModel"/> also holds references to unmanaged resources that need to be freed either with an explicit
+        /// call to Dispose() or implicitly by declaring the variable with the "using" syntax/>
+        ///
+        /// <format type="text/markdown">
+        /// <![CDATA[
+        /// [!include[io](~/../docs/samples/docs/api-reference/tensorflow-usage.md)]
+        /// ]]>
+        /// </format>
+        /// </summary>
+        /// <param name="catalog">The transform's catalog.</param>
+        /// <param name="modelLocation">Location of the TensorFlow model.</param>
+        /// <param name="treatOutputAsBatched">If the first dimension of the output is unknown, should it be treated as batched or not.</param>
+        /// <example>
+        /// <format type="text/markdown">
+        /// <![CDATA[
+        /// [!code-csharp[LoadTensorFlowModel](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/TensorFlow/TextClassification.cs)]
+        /// ]]>
+        /// </format>
+        /// </example>
+        public static TensorFlowModel LoadTensorFlowModel(this ModelOperationsCatalog catalog, string modelLocation, bool treatOutputAsBatched)
+            => TensorFlowUtils.LoadTensorFlowModel(CatalogUtils.GetEnvironment(catalog), modelLocation, treatOutputAsBatched);
     }
 }