ResNet architecture throws an error

[0xpranjal]

---

TypeError Traceback (most recent call last)
in
11 BatchNormalization(),
12 Dropout(0.3),
---> 13 Dense(1,activation="sigmoid")
14 ])
15

/opt/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
--> 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

/opt/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/sequential.py in init(self, layers, name)
114 tf_utils.assert_no_legacy_layers(layers)
115 for layer in layers:
--> 116 self.add(layer)
117
118 @Property

/opt/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
--> 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

/opt/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/sequential.py in add(self, layer)
159 raise TypeError('The added layer must be '
160 'an instance of class Layer. '
--> 161 'Found: ' + str(layer))
162
163 tf_utils.assert_no_legacy_layers([layer])

TypeError: The added layer must be an instance of class Layer. Found: <keras.engine.training.Model object at 0x7f927a019410>

[0xpranjal]

This issue can be solved by removing tf.keras in the Sequential model.