I have trained a model with keras layers and weight_normalization layer from tensorflow_addons. This is the model I trained and saved in tensorflow file format:
import tensorflow as tf
import tensorflow.keras as tk
import tensorflow_addons as tfa
model = tf.keras.Sequential([
tf.keras.layers.Input((X_train.shape[1]-1,)),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Dropout(0.2),
tfa.layers.WeightNormalization(tf.keras.layers.Dense(2048, activation="relu")),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Dropout(0.5),
tfa.layers.WeightNormalization(tf.keras.layers.Dense(1048, activation="relu")),
tf.keras.layers.BatchNormalization(),
tf.keras.layers.Dropout(0.5),
tfa.layers.WeightNormalization(tf.keras.layers.Dense(206, activation="sigmoid")),
])
(and it has no custom metrics)
from keras.callbacks import ModelCheckpoint, EarlyStopping
# autosave best Model
best_model = ModelCheckpoint("model", monitor='val_accuracy', mode='max',verbose=0, save_best_only=True)
earlystop = EarlyStopping(monitor = 'val_accuracy',
patience = 15,
mode = 'max',
verbose = 1,
restore_best_weights = True)
callbacks = [best_model, earlystop]
model.compile(loss= 'binary_crossentropy',optimizer= 'Adam',metrics= ['accuracy'])
history = model.fit(X_res, y_res, epochs=100, verbose= 2, validation_data=(X_val[X_val.columns[1:]],y_val[y_val.columns[1:]]), callbacks=callbacks)
But when I load the model it returns an error:
model = tk.models.load_model("../input/model")
--------------------------------------------------------------------------- KeyError Traceback (most recent call last) in 2 return 3 ----> 4 model = tk.models.load_model("../input/model-custom", custom_objects={'__inference_dense_layer_call_fn_1126407':f1})
/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) 216 217 # Load all other nodes and functions. --> 218 super(KerasObjectLoader, self)._load_all() 219 220 # Finish setting up layers and models. See function docstring for more info.
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in _load_all(self) 139 def _load_all(self): 140 """Loads all nodes and functions from the SavedModel and their edges.""" --> 141 self._load_nodes() 142 self._load_edges() 143 # TODO(b/124045874): There are limitations with functions whose captures
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in _load_nodes(self) 281 # interface. 282 continue --> 283 node, setter = self._recreate(proto, node_id) 284 nodes[node_id] = node 285 node_setters[node_id] = setter
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/saving/saved_model/load.py in _recreate(self, proto, node_id) 237 obj._handle_name = proto.variable.name + ':0' # pylint: disable=protected-access 238 else: --> 239 obj, setter = super(KerasObjectLoader, self)._recreate(proto, node_id) 240 return obj, setter 241
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in _recreate(self, proto, node_id) 391 if kind not in factory: 392 raise ValueError("Unknown SavedObject type: %r" % kind) --> 393 return factorykind 394 395 def _recreate_user_object(self, proto, node_id):
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in () 380 lambda: self._recreate_user_object(proto.user_object, node_id)), 381 "asset": lambda: self._recreate_asset(proto.asset), --> 382 "function": lambda: self._recreate_function(proto.function), 383 "bare_concrete_function": functools.partial( 384 self._recreate_bare_concrete_function,
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/load.py in _recreate_function(self, proto) 419 def _recreate_function(self, proto): 420 return function_deserialization.recreate_function( --> 421 proto, self._concrete_functions), setattr 422 423 def _recreate_bare_concrete_function(self, proto):
/opt/conda/lib/python3.7/site-packages/tensorflow/python/saved_model/function_deserialization.py in recreate_function(saved_function, concrete_functions) 259 concrete_function_objects = [] 260 for concrete_function_name in saved_function.concrete_functions: --> 261 concrete_function_objects.append(concrete_functions[concrete_function_name]) 262 263 for cf in concrete_function_objects:
KeyError: '__inference_dense_layer_call_fn_1126407'
Can you please help me load the model correctly.. Thanks
