def test_convert_inner_node_data(self):
data = tf_utils.convert_inner_node_data((tf_utils.ListWrapper(['l', 2, 3]),
tf_utils.ListWrapper(['l', 5, 6])))
self.assertEqual(data, (['l', 2, 3], ['l', 5, 6]))
data = tf_utils.convert_inner_node_data(((['l', 2, 3], ['l', 5, 6])),
wrap=True)
self.assertTrue(all(isinstance(ele, tf_utils.ListWrapper) for ele in data))
def serialize(self, make_node_key, node_conversion_map):
"""Serializes `Node` for Functional API's `get_config`."""
# Serialization still special-cases first argument.
args, kwargs = self.call_args, self.call_kwargs
inputs, args, kwargs = self.layer._split_out_first_arg(args, kwargs)
# Treat everything other than first argument as a kwarg.
arguments = dict(zip(self.layer._call_fn_args[1:], args))
arguments.update(kwargs)
kwargs = arguments
def _serialize_keras_tensor(t):
"""Serializes a single Tensor passed to `call`."""
if hasattr(t, '_keras_history'):
kh = t._keras_history
node_index = kh.node_index
node_key = make_node_key(kh.layer.name, node_index)
new_node_index = node_conversion_map.get(node_key, 0)
return [kh.layer.name, new_node_index, kh.tensor_index]
if isinstance(t, np.ndarray):
return t.tolist()
if isinstance(t, tf.Tensor):
return backend.get_value(t).tolist()
# Not using json_utils to serialize both constant Tensor and constant
# CompositeTensor for saving format backward compatibility.
if isinstance(t, tf.__internal__.CompositeTensor):
return (_COMPOSITE_TYPE, json_utils.Encoder().encode(t))
return t
kwargs = tf.nest.map_structure(_serialize_keras_tensor, kwargs)
try:
json.dumps(kwargs, default=json_utils.get_json_type)
except TypeError:
kwarg_types = tf.nest.map_structure(type, kwargs)
raise TypeError('Layer ' + self.layer.name +
' was passed non-JSON-serializable arguments. ' +
'Arguments had types: ' + str(kwarg_types) +
'. They cannot be serialized out '
'when saving the model.')
# `kwargs` is added to each Tensor in the first arg. This should be
# changed in a future version of the serialization format.
def serialize_first_arg_tensor(t):
if is_keras_tensor(t):
kh = t._keras_history
node_index = kh.node_index
node_key = make_node_key(kh.layer.name, node_index)
new_node_index = node_conversion_map.get(node_key, 0)
data = [kh.layer.name, new_node_index, kh.tensor_index, kwargs]
else:
# If an element in the first call argument did not originate as a
# keras tensor and is a constant value, we save it using the format
# ['_CONSTANT_VALUE', -1, serialized_tensor_or_python_constant]
# (potentially including serialized kwargs in an optional 4th argument).
data = [
_CONSTANT_VALUE, -1,
_serialize_keras_tensor(t), kwargs
]
return tf_utils.ListWrapper(data)
data = tf.nest.map_structure(serialize_first_arg_tensor, inputs)
if (not tf.nest.is_nested(data)
and not self.layer._preserve_input_structure_in_config):
data = [data]
data = tf_utils.convert_inner_node_data(data)
return data