Building model with https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/3
NotEncodableErrorTraceback (most recent call last)
<ipython-input-18-ec7885f2f9d5> in <module>()
2 model = tf.keras.Sequential([
3 hub.KerasLayer(MODULE_HANDLE, output_shape=[FV_SIZE],
----> 4 trainable=do_fine_tuning),
5 tf.keras.layers.Dropout(rate=0.2),
6 tf.keras.layers.Dense(train_generator.num_classes, activation='softmax',
11 frames
/usr/local/lib/python2.7/dist-packages/tensorflow_hub/keras_layer.pyc in __init__(self, handle, trainable, arguments, **kwargs)
96 self._func = handle
97 else:
---> 98 self._func = module_v2.load(handle)
99 if not callable(self._func):
100 raise ValueError("Non-callable result from hub.load('%s')" %
/usr/local/lib/python2.7/dist-packages/tensorflow_hub/module_v2.pyc in load(handle)
78 "format. Loading of the module using "
79 "hub.load() is not supported." % handle)
---> 80 return tf_v1.saved_model.load_v2(module_handle)
81 else:
82 raise NotImplementedError("hub.load() is not implemented for TF < 1.14.x, "
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in load(export_dir, tags)
322 loader = _Loader(object_graph_proto,
323 saved_model_proto,
--> 324 export_dir)
325 root = loader.get(0)
326 else:
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in __init__(self, object_graph_proto, saved_model_proto, export_dir)
55 function_deserialization.load_function_def_library(
56 meta_graph.graph_def.library))
---> 57 self._load_all()
58 # TODO(b/124045874): There are limitations with functions whose captures
59 # trigger other functions to be executed. For now it is only guaranteed to
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in _load_all(self)
130 node_setters = []
131 for proto in self._proto.nodes:
--> 132 node, setter = self._recreate(proto)
133 self._nodes.append(node)
134 node_setters.append(setter)
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in _recreate(self, proto)
193 if kind not in factory:
194 raise ValueError("Unknown SavedObject type: %r" % kind)
--> 195 return factory[kind]()
196
197 def _recreate_user_object(self, proto):
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in <lambda>()
182 "user_object": lambda: self._recreate_user_object(proto.user_object),
183 "asset": lambda: self._recreate_asset(proto.asset),
--> 184 "function": lambda: self._recreate_function(proto.function),
185 "bare_concrete_function": functools.partial(
186 self._recreate_bare_concrete_function,
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/load.pyc in _recreate_function(self, proto)
217 def _recreate_function(self, proto):
218 return function_deserialization.recreate_function(
--> 219 proto, self._concrete_functions), setattr
220
221 def _recreate_bare_concrete_function(self, proto):
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/function_deserialization.pyc in recreate_function(saved_function, concrete_functions)
184 coder = nested_structure_coder.StructureCoder()
185 function_spec = _deserialize_function_spec(saved_function.function_spec,
--> 186 coder)
187
188 def restored_function_body(*args, **kwargs):
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/function_deserialization.pyc in _deserialize_function_spec(function_spec_proto, coder)
118 annotations=typeless_fullargspec.annotations)
119 is_method = function_spec_proto.is_method
--> 120 args_to_prepend = coder.decode_proto(function_spec_proto.args_to_prepend)
121 kwargs_to_include = coder.decode_proto(function_spec_proto.kwargs_to_include)
122 input_signature = coder.decode_proto(function_spec_proto.input_signature)
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/nested_structure_coder.pyc in decode_proto(self, proto)
112 NotEncodableError: For values for which there are no encoders.
113 """
--> 114 return self._map_structure(proto, self._get_decoders())
115
116
/usr/local/lib/python2.7/dist-packages/tensorflow/python/saved_model/nested_structure_coder.pyc in _map_structure(self, pyobj, coders)
69 return do(pyobj, recursion_fn)
70 raise NotEncodableError(
---> 71 "No encoder for object [%s] of type [%s]." % (str(pyobj), type(pyobj)))
72
73 def encode_structure(self, nested_structure):
NotEncodableError: No encoder for object [] of type [<class 'tensorflow.core.protobuf.struct_pb2.StructuredValue'>].
tried this notebook from issue #287
it is giving me the following error: