diff --git a/verif/frameworks/test_builder.py b/verif/frameworks/test_builder.py
index fcd72a3..3554e40 100644
--- a/verif/frameworks/test_builder.py
+++ b/verif/frameworks/test_builder.py
@@ -1175,7 +1175,7 @@
 
             return result[0]
 
-    class LSTM:
+    class LSTM(tf.Module):
         def __init__(self, name):
             self.result_name = name
             self.lstm = tf.keras.layers.LSTM(
@@ -1191,6 +1191,23 @@
         def eval(self, a):
             return self.lstm(a)
 
+    class SLSTM(tf.Module):
+        def __init__(self, name):
+            self.result_name = name
+            self.lstm = tf.keras.layers.LSTM(
+                2,
+                stateful=True,
+                activation="tanh",
+                unroll=False,
+                recurrent_activation="sigmoid",
+                use_bias=True,
+                recurrent_initializer="ones",
+                kernel_initializer="ones",
+            )
+
+        def eval(self, a):
+            return self.lstm(a)
+
     class GRU:
         def __init__(self, name):
             self.result_name = name
@@ -1256,3 +1273,22 @@
 
         def eval(self, a):
             return tf.broadcast_to(a, shape=self.shape, name=self.result_name)
+
+    class CallOnce(tf.Module):
+        def __init__(self, name):
+            print(tf.__version__)
+            self.result_name = name
+            self.var = tf.Variable([1.0])
+
+        @tf.function(
+            input_signature=[
+                tf.TensorSpec(
+                    shape=[
+                        1,
+                    ],
+                    dtype=tf.float32,
+                )
+            ]
+        )
+        def eval(self, a):
+            return self.var.assign([2.0])
diff --git a/verif/frameworks/tosa_verif_framework_generator.py b/verif/frameworks/tosa_verif_framework_generator.py
index ec009c6..ffe373b 100755
--- a/verif/frameworks/tosa_verif_framework_generator.py
+++ b/verif/frameworks/tosa_verif_framework_generator.py
@@ -28,6 +28,7 @@
     get_tf_dtype,
     get_shape_str,
 )  # noqa: E402
+
 from tensorflow.lite.python.interpreter import OpResolverType  # noqa: E402
 
 # All of the supported frameworks
@@ -829,6 +830,15 @@
             ]
         },
     },
+    "lstm_stateful": {
+        "operands": (1, 0),
+        "build_fcn": (TBuilder.SLSTM, TGen.tgRecurrent, ArgGen.agNone),
+        "types": {
+            "tflite": [
+                tf.float32,
+            ]
+        },
+    },
     "gru": {
         "operands": (1, 0),
         "build_fcn": (TBuilder.GRU, TGen.tgRecurrent, ArgGen.agNone),
@@ -848,6 +858,17 @@
             ]
         },
     },
+    "callonce": {
+        "operands": (1, 0),
+        "build_fcn": (TBuilder.CallOnce, TGen.tgBasic, ArgGen.agNone),
+        "types": {
+            "tflite": [tf.float32],
+        },
+        "custom_shapes": {
+            "custom_shape_only": True,
+            "shape_list": [(1,)],
+        },
+    },
     "rfft2d": {
         "operands": (1, 0),
         "build_fcn": (TBuilder.RFFT2d, TGen.tgRFFT2d, ArgGen.agRFFT2d),
@@ -1219,9 +1240,15 @@
             if "tflite" not in excluded_framework_list:
                 # Convert the model to TFLite flatbuffer
                 module = tf.Module()
-                converter = tf.lite.TFLiteConverter.from_concrete_functions(
-                    [concrete_function], module
-                )
+
+                if op_name == "callonce" or op_name == "lstm_stateful":
+                    converter = tf.lite.TFLiteConverter.from_concrete_functions(
+                        [concrete_function], fcn_node
+                    )
+                else:
+                    converter = tf.lite.TFLiteConverter.from_concrete_functions(
+                        [concrete_function], module
+                    )
 
                 converter.experimental_new_converter = True