def __init__(self, layer):
self.layer = layer
self.layer_call_method = _get_layer_call_method(layer)
self._expects_training_arg = utils.layer_uses_training_bool(layer)
self._call_spec = layer._call_spec # pylint: disable=protected-access
# Create new call spec if the layer itself does not accept a training arg,
# but one of its child layers does. When this layer's call functions are
# traced, they will be traced with an added `training` keyword argument.
if (not self.layer._expects_training_arg
and self._expects_training_arg): # pylint: disable=protected-access
arg_spec = utils.set_training_arg_spec(
self._call_spec.full_argspec, False)
self._call_spec = layer_utils.CallFunctionSpec(arg_spec)
self._layer_inputs = self._get_layer_inputs(layer)
self._functions = weakref.WeakValueDictionary()
# Get the input argument name from the args.
if self._call_spec.arg_names:
self._input_arg_name = self._call_spec.arg_names[0]
else:
# Layer could be defined with only varargs, in which case use a default
# name.
self._input_arg_name = "inputs"
def __init__(self, layer):
self.layer = layer
self.layer_call_method = _get_layer_call_method(layer)
self._expects_training_arg = utils.layer_uses_training_bool(layer)
self._training_arg_index = utils.get_training_arg_index(
self.layer_call_method)
# If the layer call function has kwargs, then the traced function cannot
# have an input signature.
arg_spec = tf_inspect.getfullargspec(self.layer_call_method)
self._has_kwargs = bool(self._expects_training_arg or
arg_spec.defaults or
arg_spec.kwonlyargs or
arg_spec.varkw)
self._input_signature = self._generate_input_signature(layer)
self._functions = weakref.WeakValueDictionary()
# Bool indicating whether this object is currently tracing the layer call
# functions.
self.tracing = False
# Get the input argument name from the args.
args = arg_spec.args
if tf_inspect.ismethod(self.layer_call_method):
args = args[1:]
self._input_arg_name = args[0] if args else 'inputs'
def __init__(self, layer):
self.layer = layer
self.layer_call_method = _get_layer_call_method(layer)
self._expects_training_arg = utils.layer_uses_training_bool(layer)
self._training_arg_index = utils.get_training_arg_index(
self.layer_call_method)
self._layer_inputs = self._get_layer_inputs(layer)
self._functions = weakref.WeakValueDictionary()
# Get the input argument name from the args.
arg_spec = tf_inspect.getfullargspec(self.layer_call_method)
args = arg_spec.args
if tf_inspect.ismethod(self.layer_call_method):
args = args[1:]
self._input_arg_name = args[0] if args else 'inputs'