diff --git a/src/tacotron_main.rs b/src/tacotron_main.rs
index 35c27413ad..587c0458c9 100644
--- a/src/tacotron_main.rs
+++ b/src/tacotron_main.rs
@@ -2,12 +2,22 @@ extern crate tensorflow;
 
 pub mod model;
 
-use tensorflow::Graph;
-use tensorflow::Session;
-use tensorflow::SessionOptions;
+use tensorflow::{
+  SessionOptions,
+  Session,
+  Graph,
+  Tensor,
+  SessionRunArgs
+};
 
 use model::print_tensorfow_version;
 
+const INPUT_NAME : &'static str = "inputs";
+const INPUT_LENGTHS_NAME : &'static str = "inputs_lengths";
+
+// Tensor("model/griffinlim/Squeeze:0", shape=(?,), dtype=float32)
+const OUTPUT_NAME : &'static str = "model/griffinlim/Squeeze";
+
 /**
  * To save:
      print('Saving model...')
@@ -23,6 +33,11 @@ use model::print_tensorfow_version;
     )
 
     builder.save()
+
+    # Save the model text labels to dereference
+    definition = self.session.graph_def
+    directory = 'saved_model_labels'
+    tf.train.write_graph(definition, directory, 'model_labels.pb', as_text=True)
  */
 pub fn main() {
   println!("Tacotron");
@@ -38,5 +53,62 @@ pub fn main() {
     dir_name,
   ).expect("Should load");
 
-  println!("Loaded!");
+  println!("Model Loaded!");
+
+  let mut input = Tensor::new(&[1, 24, 10])
+      .with_values(&[
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+        0.0f32, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+      ])
+      .unwrap();
+
+  println!(">>> Input tensor dims: {:?}", input.dims());
+
+    {
+        let mut args = SessionRunArgs::new();
+
+        // input_A_test:
+        // Tensor("input_A_test:0", shape=(?, 24, ?), dtype=float32)
+        args.add_feed(&graph.operation_by_name_required(INPUT_NAME)
+            .expect(INPUT_NAME), 0, &input);
+
+        args.add_feed(&graph.operation_by_name_required(INPUT_NAME)
+            .expect(INPUT_LENGTHS_NAME), 0, &input);
+
+        // generation_B_test:
+        // Tensor("generator_A2B_3/output_transpose:0", shape=(?, 24, ?), dtype=float32)
+        let z = args.request_fetch(
+            &graph.operation_by_name_required(OUTPUT_NAME)
+                .expect(OUTPUT_NAME), 0);
+
+        session.run(&mut args).expect("Run success");
+
+        // Check our results.
+        let z_res = args.fetch::<f32>(z).expect("ret");
+
+        println!("z_rez.dims(): {:?}", z_res.dims());
+        println!("z_rez: {:?}", z_res);
+    }
 }
\ No newline at end of file