Split merged TFLiteConverter implementations into frozen graph converter and saved model converter

PiperOrigin-RevId: 310301390
Change-Id: I021c1fa678d6367226e1a19e646bb6d0ff9769e3

tensorflow/lite/python/lite_test.py

@@ -2318,5 +2318,42 @@ class ImportOpsUtilTest(LiteTest):
     self.assertIsNotNone(lite.get_potentially_supported_ops())
 
 
+class DefaultConverterAttrsTest(LiteTest):
+
+  def testAttrs(self):
+    with ops.Graph().as_default():
+      in_tensor = array_ops.placeholder(shape=[2, 2], dtype=dtypes.float32)
+      out_tensor = in_tensor + in_tensor
+      sess = session.Session()
+
+    # Convert model.
+    converter = lite.TFLiteConverter.from_session(sess, [in_tensor],
+                                                  [out_tensor])
+
+    # Assert output format.
+    self.assertEqual(converter.output_format, lite_constants.TFLITE)
+
+    # Assert the default inference type is float.
+    self.assertEqual(converter.inference_type, lite_constants.FLOAT)
+
+    # Assert the default inference type overrides are None.
+    self.assertIsNone(converter.inference_input_type)
+    self.assertIsNone(converter.inference_output_type)
+
+    # Assert the default quantization options are not set.
+    self.assertEqual(converter.quantized_input_stats, {})
+    self.assertIsNone(converter.default_ranges_stats)
+    self.assertFalse(converter.reorder_across_fake_quant)
+    self.assertFalse(converter.change_concat_input_ranges)
+
+    # Assert dropping control dependency is enabled by default.
+    self.assertTrue(converter.drop_control_dependency)
+
+    # Assert dumping extra information is disabled by default.
+    self.assertIsNone(converter.dump_graphviz_dir)
+    self.assertFalse(converter.dump_graphviz_video)
+    self.assertIsNone(converter.conversion_summary_dir)
+
+
 if __name__ == '__main__':
   test.main()

tensorflow/lite/python/lite_v2_test.py

@@ -981,6 +981,27 @@ class UnknownShapes(lite_v2_test_util.ModelTest):
     np.testing.assert_almost_equal(
         expected_value.numpy(), actual_value[0], decimal=4)
 
+  def testSizeInvalid(self):
+
+    @tf.function(input_signature=[
+        tf.TensorSpec(shape=[1, None, 16, 3], dtype=tf.float32)
+    ])
+    def model(in_tensor):
+      return in_tensor + in_tensor
+
+    concrete_func = model.get_concrete_function()
+
+    # Test invalid shape. None after 1st dimension. Run with TOCO in order to
+    # invoke shape checking code.
+    converter = lite.TFLiteConverterV2.from_concrete_functions([concrete_func])
+    converter.experimental_new_converter = False
+    with self.assertRaises(ValueError) as error:
+      converter.convert()
+    self.assertEqual(
+        'None is only supported in the 1st dimension. Tensor '
+        '\'in_tensor\' has invalid shape \'[1, None, 16, 3]\'.',
+        str(error.exception))
+
 
 if __name__ == '__main__':
   test.main()

tensorflow/tools/api/golden/v1/tensorflow.lite.-t-f-lite-converter.pbtxt

@@ -1,11 +1,13 @@
 path: "tensorflow.lite.TFLiteConverter"
 tf_class {
   is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverter\'>"
+  is_instance: "<class \'tensorflow.lite.python.lite.TFLiteFrozenGraphConverter\'>"
+  is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverterBaseV1\'>"
   is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverterBase\'>"
   is_instance: "<type \'object\'>"
   member_method {
     name: "__init__"
-    argspec: "args=[\'self\', \'graph_def\', \'input_tensors\', \'output_tensors\', \'input_arrays_with_shape\', \'output_arrays\', \'experimental_debug_info_func\', \'saved_model_dir\', \'saved_model_tags\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+    argspec: "args=[\'self\', \'graph_def\', \'input_tensors\', \'output_tensors\', \'input_arrays_with_shape\', \'output_arrays\', \'experimental_debug_info_func\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
   }
   member_method {
     name: "convert"

tensorflow/tools/api/golden/v2/tensorflow.lite.-t-f-lite-converter.pbtxt

@@ -1,11 +1,13 @@
 path: "tensorflow.lite.TFLiteConverter"
 tf_class {
   is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverterV2\'>"
+  is_instance: "<class \'tensorflow.lite.python.lite.TFLiteFrozenGraphConverterV2\'>"
+  is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverterBaseV2\'>"
   is_instance: "<class \'tensorflow.lite.python.lite.TFLiteConverterBase\'>"
   is_instance: "<type \'object\'>"
   member_method {
     name: "__init__"
-    argspec: "args=[\'self\', \'funcs\', \'trackable_obj\', \'saved_model_dir\', \'saved_model_tags\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+    argspec: "args=[\'self\', \'funcs\', \'trackable_obj\'], varargs=None, keywords=None, defaults=[\'None\'], "
   }
   member_method {
     name: "convert"