Saving and loading a model in TensorFlow 2.3.1...
import tensorflow as tf
model1 = tf.keras.Sequential([
tf.keras.layers.Input(shape = (81,), dtype = 'uint8'),
tf.keras.layers.Lambda(tf.keras.backend.one_hot, arguments={'num_classes': 10}, output_shape=(81, 10)),
])
tf.keras.models.save_model(model1, './model')
model2 = tf.keras.models.load_model('./model')
model2.summary()
causes a rather long exception, quoted in full below. It seems to be the Lambda layer that causes issues; save-loading works fine without it. I've tried adding custom_objects={'one_hot' : tf.keras.backend.one_hot} and suchlike to the load call, but it doesn't fix it. I'd be very grateful if anyone had a workaround for this.
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/backend.py in wrapper(*args, **kwargs)
200 try:
--> 201 return target(*args, **kwargs)
202 except (TypeError, ValueError):
TypeError: 'str' object is not callable
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
<ipython-input-20-77668ee9d9b2> in <module>
7
8 tf.keras.models.save_model(model1, './model')
----> 9 model2 = tf.keras.models.load_model('./model', custom_objects={'tf.keras.backend.one_hot' : tf.keras.backend.one_hot})
10 model2.summary()
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/save.py in load_model(filepath, custom_objects, compile, options)
185 if isinstance(filepath, six.string_types):
186 loader_impl.parse_saved_model(filepath)
--> 187 return saved_model_load.load(filepath, compile, options)
188
189 raise IOError(
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in load(path, compile, options)
119
120 model = tf_load.load_internal(
--> 121 path, options=options, loader_cls=KerasObjectLoader)
122
123 # pylint: disable=protected-access
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in load_internal(export_dir, tags, options, loader_cls)
631 try:
632 loader = loader_cls(object_graph_proto, saved_model_proto, export_dir,
--> 633 ckpt_options)
634 except errors.NotFoundError as err:
635 raise FileNotFoundError(
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in __init__(self, *args, **kwargs)
192 self._models_to_reconstruct = []
193
--> 194 super(KerasObjectLoader, self).__init__(*args, **kwargs)
195
196 # Now that the node object has been fully loaded, and the checkpoint has
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in __init__(self, object_graph_proto, saved_model_proto, export_dir, ckpt_options)
128 self._concrete_functions[name] = _WrapperFunction(concrete_function)
129
--> 130 self._load_all()
131 self._restore_checkpoint()
132
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in _load_all(self)
219
220 # Finish setting up layers and models. See function docstring for more info.
--> 221 self._finalize_objects()
222
223 @property
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in _finalize_objects(self)
528
529 # Initialize graph networks, now that layer dependencies have been resolved.
--> 530 self._reconstruct_all_models()
531
532 def _unblock_model_reconstruction(self, layer_id, layer):
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in _reconstruct_all_models(self)
546 all_initialized_models.add(model_id)
547 model, layers = self.model_layer_dependencies[model_id]
--> 548 self._reconstruct_model(model_id, model, layers)
549 self._add_object_graph_edges(self._proto.nodes[model_id], model_id)
550 _finalize_config_layers([model])
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in _reconstruct_model(self, model_id, model, layers)
576 dtype=layers[0].dtype,
577 name=layers[0].name + '_input'))
--> 578 model.__init__(layers, name=config['name'])
579 if not model.inputs:
580 first_layer = self._get_child_layer_node_ids(model_id, model.name)[0]
/opt/conda/lib/python3.7/site-packages/tensorflow/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/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py in __init__(self, layers, name)
140 layers = [layers]
141 for layer in layers:
--> 142 self.add(layer)
143
144 @property
/opt/conda/lib/python3.7/site-packages/tensorflow/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/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py in add(self, layer)
219 # If the model is being built continuously on top of an input layer:
220 # refresh its output.
--> 221 output_tensor = layer(self.outputs[0])
222 if len(nest.flatten(output_tensor)) != 1:
223 raise ValueError(SINGLE_LAYER_OUTPUT_ERROR_MSG)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
924 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
925 return self._functional_construction_call(inputs, args, kwargs,
--> 926 input_list)
927
928 # Maintains info about the `Layer.call` stack.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
1115 try:
1116 with ops.enable_auto_cast_variables(self._compute_dtype_object):
-> 1117 outputs = call_fn(cast_inputs, *args, **kwargs)
1118
1119 except errors.OperatorNotAllowedInGraphError as e:
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py in call(self, inputs, mask, training)
901 with backprop.GradientTape(watch_accessed_variables=True) as tape,
902 variable_scope.variable_creator_scope(_variable_creator):
--> 903 result = self.function(inputs, **kwargs)
904 self._check_variables(created_variables, tape.watched_variables())
905 return result
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/backend.py in wrapper(*args, **kwargs)
203 # Note: convert_to_eager_tensor currently raises a ValueError, not a
204 # TypeError, when given unexpected types. So we need to catch both.
--> 205 result = dispatch(wrapper, args, kwargs)
206 if result is not OpDispatcher.NOT_SUPPORTED:
207 return result
TypeError: 'module' object is not callable
question from:
https://stackoverflow.com/questions/65883675/keras-raises-an-exception-on-loading-a-lambda-layer 
