Tensorflow GetModelSchema should support unfrozen models

src/Microsoft.ML.TensorFlow/TensorFlow/TensorflowUtils.cs

@@ -75,27 +75,25 @@ internal static Schema GetModelSchema(IExceptionContext ectx, TFGraph graph, str
         /// of kind <see cref="OpType"/>, indicating the operation type of the node, and if that node has inputs in the graph,
         /// it contains metadata of kind <see cref="InputOps"/>, indicating the names of the input nodes.
         /// </summary>
-        /// <param name="ectx">An <see cref="IExceptionContext"/>.</param>
-        /// <param name="modelFile">The name of the file containing the TensorFlow model. Currently only frozen model
-        /// format is supported.</param>
-        public static Schema GetModelSchema(IExceptionContext ectx, string modelFile)
+        /// <param name="env">The environment to use.</param>
+        /// <param name="modelPath">Model to load.</param>
+        public static Schema GetModelSchema(IHostEnvironment env, string modelPath)
         {
-            var bytes = File.ReadAllBytes(modelFile);
-            var session = LoadTFSession(ectx, bytes, modelFile);
-            return GetModelSchema(ectx, session.Graph);
+            var model = LoadTensorFlowModel(env, modelPath);
+            return GetModelSchema(env, model.Session.Graph);
         }
 
         /// <summary>
         /// This is a convenience method for iterating over the nodes of a TensorFlow model graph. It
-        /// iterates over the columns of the <see cref="ISchema"/> returned by <see cref="GetModelSchema(IExceptionContext, string)"/>,
+        /// iterates over the columns of the <see cref="ISchema"/> returned by <see cref="GetModelSchema(IHostEnvironment, string)"/>,
         /// and for each one it returns a tuple containing the name, operation type, column type and an array of input node names.
         /// This method is convenient for filtering nodes based on certain criteria, for example, by the operation type.
         /// </summary>
-        /// <param name="modelFile"></param>
+        /// <param name="modelPath">Model to load.</param>
         /// <returns></returns>
-        public static IEnumerable<(string, string, ColumnType, string[])> GetModelNodes(string modelFile)
+        public static IEnumerable<(string, string, ColumnType, string[])> GetModelNodes(string modelPath)
         {
-            var schema = GetModelSchema(null, modelFile);
+            var schema = GetModelSchema(new MLContext(), modelPath);
 
             for (int i = 0; i < schema.Count; i++)
             {
@@ -310,6 +308,12 @@ private static void CreateTempDirectoryWithAcl(string folder, string identity)
             }
         }
 
+        /// <summary>
+        /// Load TensorFlow model into memory.
+        /// </summary>
+        /// <param name="env">The environment to use.</param>
+        /// <param name="modelPath">The model to load.</param>
+        /// <returns></returns>
         public static TensorFlowModelInfo LoadTensorFlowModel(IHostEnvironment env, string modelPath)
         {
             var session = GetSession(env, modelPath);

test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs

@@ -606,8 +606,9 @@ public void TensorFlowTransformCifar()
         public void TensorFlowTransformCifarSavedModel()
         {
             var modelLocation = "cifar_saved_model";
-
             var mlContext = new MLContext(seed: 1, conc: 1);
+            var loadModelSchema = TensorFlowUtils.GetModelSchema(mlContext, modelLocation);
+            Assert.Equal(335, loadModelSchema.Count);
             var tensorFlowModel = TensorFlowUtils.LoadTensorFlowModel(mlContext, modelLocation);
             var schema = tensorFlowModel.GetInputSchema();
             Assert.True(schema.TryGetColumnIndex("Input", out int column));