I am able to load the model saved_model.pb found in saved_model folder in the pre-trained directory using:
tf.saved_model.load
However when using:
tf.keras.models.load_model
I get the error:

WARNING:tensorflow:SavedModel saved prior to TF 2.5 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), NOT tf.saved_model.save(). To confirm, there should be a file named “keras_metadata.pb” in the SavedModel directory.
/usr/local/lib/python3.7/dist-packages/keras/layers/core/lambda_layer.py:299: UserWarning: google3.third_party.tensorflow.python.ops.nn_ops is not loaded, but a Lambda layer uses it. It may cause errors.
‘function_type’)
/usr/local/lib/python3.7/dist-packages/keras/layers/core/lambda_layer.py:299: UserWarning: google3.third_party.tensorflow_models.object_detection.models.feature_map_generators is not loaded, but a Lambda layer uses it. It may cause errors.
‘function_type’)
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
 in ()
----> 1 model = tf.keras.models.load_model("/content/tensorflow/workspace/pre-trained/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model")
1 frames
/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
65     except Exception as e:  # pylint: disable=broad-except
66       filtered_tb = _process_traceback_frames(e.traceback)
—> 67       raise e.with_traceback(filtered_tb) from None
68     finally:
69       del filtered_tb
/usr/local/lib/python3.7/dist-packages/keras/layers/core/lambda_layer.py in wrapper(*args, **kwargs)
203       # don’t want to incur the runtime cost of assembling any state used for
204       # checking only to immediately discard it.
 → 205       return
206
207     tracked_weights = set(v.ref() for v in self.weights)
NameError: Exception encountered when calling layer “Conv1_relu” (type Lambda).
name ‘dispatch’ is not defined
Call arguments received:
• inputs=tf.Tensor(shape=(None, None, None, 32), dtype=float32)
• mask=None
• training=None

I am not sure why I am getting this error.
Using the first method for loading in the model, I am unsure of how to extract information about which layers are lambda layers. I am also unsure of how to manipulate this model so that the lambda layers are replaced with tf.keras.layers.Layer instead. How can I do this? Thanks.