The from_tflite() function should accept None as default value of input_names and output_names. (#1967)

* The from_tflite() function should not change the value of None to an empty list for input_names and output_names.
* Change the way to validate a list is None or Emtpy.

Signed-off-by: Jay Zhang <[email protected]>

Author: fatcat-z

tests/test_api.py

@@ -237,11 +237,27 @@ def test_tflite(self):
 
         x_val = np.array([1.0, 2.0, -3.0, -4.0], dtype=np.float32).reshape((2, 2))
         model_proto, _ = tf2onnx.convert.from_tflite("tests/models/regression/tflite/test_api_model.tflite",
-                                                     input_names=['input'], output_names=['output'],
+                                                     input_names=["input"], output_names=["output"],
                                                      output_path=output_path)
-        output_names = [n.name for n in model_proto.graph.output]
-        oy = self.run_onnxruntime(output_path, {"input": x_val}, output_names)
-        self.assertTrue(output_names[0] == "output")
+        actual_output_names = [n.name for n in model_proto.graph.output]
+        oy = self.run_onnxruntime(output_path, {"input": x_val}, actual_output_names)
+
+        self.assertTrue(actual_output_names[0] == "output")
+        exp_result = tf.add(x_val, x_val)
+        self.assertAllClose(exp_result, oy[0], rtol=0.1, atol=0.1)
+
+    @check_tf_min_version("2.0")
+    def test_tflite_without_input_output_names(self):
+        output_path = os.path.join(self.test_data_directory, "model.onnx")
+
+        x_val = np.array([1.0, 2.0, -3.0, -4.0], dtype=np.float32).reshape((2, 2))
+        model_proto, _ = tf2onnx.convert.from_tflite("tests/models/regression/tflite/test_api_model.tflite",
+                                                     output_path=output_path)
+        actual_input_names = [n.name for n in model_proto.graph.input]
+        actual_output_names = [n.name for n in model_proto.graph.output]
+        oy = self.run_onnxruntime(output_path, {actual_input_names[0]: x_val}, output_names=None)
+
+        self.assertTrue(actual_output_names[0] == "output")
         exp_result = tf.add(x_val, x_val)
         self.assertAllClose(exp_result, oy[0], rtol=0.1, atol=0.1)
 

tf2onnx/convert.py

@@ -663,10 +663,6 @@ def from_tflite(tflite_path, input_names=None, output_names=None, opset=None, cu
     """
     if not tflite_path:
         raise ValueError("tflite_path needs to be provided")
-    if not input_names:
-        input_names = []
-    if not output_names:
-        output_names = []
 
     with tf.device("/cpu:0"):
         model_proto, external_tensor_storage = _convert_common(

tf2onnx/tflite_utils.py

@@ -156,9 +156,9 @@ def graphs_from_tflite(tflite_path, input_names=None, output_names=None):
         if is_main_g:
             # Override IO in main graph
             utils.check_io(input_names, output_names, output_shapes.keys())
-            if input_names is not None:
+            if input_names:
                 g_inputs = input_names
-            if output_names is not None:
+            if output_names:
                 g_outputs = output_names
         g = Graph(onnx_nodes, output_shapes, dtypes, input_names=g_inputs, output_names=g_outputs,
                   is_subgraph=not is_main_g, graph_name=graph_name)