diff --git a/src/liquid_audio/model/conformer/encoder.py b/src/liquid_audio/model/conformer/encoder.py
index 2b31c05..d3a8f59 100644
--- a/src/liquid_audio/model/conformer/encoder.py
+++ b/src/liquid_audio/model/conformer/encoder.py
@@ -215,60 +215,6 @@ def input_example(self, max_batch=1, max_dim=256):
 
         return all_input_example
 
-    @property
-    def input_types(self):
-        """Returns definitions of module input ports."""
-        return OrderedDict(
-            {
-                "audio_signal": NeuralType(('B', 'D', 'T'), SpectrogramType()),
-                "length": NeuralType(tuple('B'), LengthsType()),
-                "cache_last_channel": NeuralType(('D', 'B', 'T', 'D'), ChannelType(), optional=True),
-                "cache_last_time": NeuralType(('D', 'B', 'D', 'T'), ChannelType(), optional=True),
-                "cache_last_channel_len": NeuralType(tuple('B'), LengthsType(), optional=True),
-                "bypass_pre_encode": NeuralType(tuple(), BoolType(), optional=True),
-            }
-        )
-
-    @property
-    def input_types_for_export(self):
-        """Returns definitions of module input ports."""
-        return OrderedDict(
-            {
-                "audio_signal": NeuralType(('B', 'D', 'T'), SpectrogramType()),
-                "length": NeuralType(tuple('B'), LengthsType()),
-                "cache_last_channel": NeuralType(('B', 'D', 'T', 'D'), ChannelType(), optional=True),
-                "cache_last_time": NeuralType(('B', 'D', 'D', 'T'), ChannelType(), optional=True),
-                "cache_last_channel_len": NeuralType(tuple('B'), LengthsType(), optional=True),
-                "bypass_pre_encode": NeuralType(tuple(), BoolType(), optional=True),
-            }
-        )
-
-    @property
-    def output_types(self):
-        """Returns definitions of module output ports."""
-        return OrderedDict(
-            {
-                "outputs": NeuralType(('B', 'D', 'T'), AcousticEncodedRepresentation()),
-                "encoded_lengths": NeuralType(tuple('B'), LengthsType()),
-                "cache_last_channel_next": NeuralType(('D', 'B', 'T', 'D'), ChannelType(), optional=True),
-                "cache_last_time_next": NeuralType(('D', 'B', 'D', 'T'), ChannelType(), optional=True),
-                "cache_last_channel_next_len": NeuralType(tuple('B'), LengthsType(), optional=True),
-            }
-        )
-
-    @property
-    def output_types_for_export(self):
-        """Returns definitions of module output ports."""
-        return OrderedDict(
-            {
-                "outputs": NeuralType(('B', 'D', 'T'), AcousticEncodedRepresentation()),
-                "encoded_lengths": NeuralType(tuple('B'), LengthsType()),
-                "cache_last_channel_next": NeuralType(('B', 'D', 'T', 'D'), ChannelType(), optional=True),
-                "cache_last_time_next": NeuralType(('B', 'D', 'D', 'T'), ChannelType(), optional=True),
-                "cache_last_channel_next_len": NeuralType(tuple('B'), LengthsType(), optional=True),
-            }
-        )
-
     @property
     def disabled_deployment_input_names(self):
         if not self.export_cache_support:
diff --git a/src/liquid_audio/model/conformer/processor.py b/src/liquid_audio/model/conformer/processor.py
index c461b5d..0adccf0 100644
--- a/src/liquid_audio/model/conformer/processor.py
+++ b/src/liquid_audio/model/conformer/processor.py
@@ -149,32 +149,6 @@ def save_to(self, save_path: str):
     def restore_from(cls, restore_path: str):
         pass
 
-    @property
-    def input_types(self):
-        """Returns definitions of module input ports."""
-        return {
-            "input_signal": NeuralType(('B', 'T'), AudioSignal(freq=self._sample_rate)),
-            "length": NeuralType(
-                tuple('B'), LengthsType()
-            ),  # Please note that length should be in samples not seconds.
-        }
-
-    @property
-    def output_types(self):
-        """Returns definitions of module output ports.
-
-        processed_signal:
-            0: AxisType(BatchTag)
-            1: AxisType(MelSpectrogramSignalTag)
-            2: AxisType(ProcessedTimeTag)
-        processed_length:
-            0: AxisType(BatchTag)
-        """
-        return {
-            "processed_signal": NeuralType(('B', 'D', 'T'), MelSpectrogramType()),
-            "processed_length": NeuralType(tuple('B'), LengthsType()),
-        }
-
     def __init__(
         self,
         sample_rate=16000,