def generate_missing_names(self):
name_generator = utils.NameGenerator(used_names=set(t.name for t in self.tensors if t.name))
for t in self.tensors:
if not t.name:
if self.input_ids is not None and t in self.inputs:
t.name = name_generator.get_new_name(self.input_ids[list(self.inputs).index(t)])
elif self.output_ids is not None and t in self.outputs:
t.name = name_generator.get_new_name(self.output_ids[list(self.outputs).index(t)])
elif t.is_variable:
t.name = name_generator.get_new_name('variable')
elif t.is_constant:
t.name = name_generator.get_new_name('constant')
elif t.producer is None:
t.name = name_generator.get_new_name('external')
else:
t.name = name_generator.get_new_name(t.producer.name)
label_generator = utils.NameGenerator(used_names=set(t.label for t in self.tensors if t.label))
for t in self.tensors:
if t.is_variable and not t.label:
t.label = label_generator.get_new_name('variable')
if not self.name:
self.name = "network"
def _generate_names(graph):
ng = utils.NameGenerator()
names = {}
for op in graph.operations:
new_name = ng.get_new_name(op.name)
names[op] = new_name
for i, tensor in enumerate(op.outputs):
if i == 0:
names[tensor] = new_name
else:
names[tensor] = new_name + ':' + str(i)
for tensor in graph.tensors:
if tensor.producer is None:
if tensor.data is None:
if tensor in graph.inputs and graph.input_ids:
names[tensor] = ng.get_new_name(graph.input_ids[graph.inputs.index(tensor)])
else:
names[tensor] = ng.get_new_name('Placeholder')
elif isinstance(tensor.data, np.ndarray):
if tensor.label:
names[tensor] = ng.get_new_name(tensor.label)
else:
names[tensor] = ng.get_new_name('Variable')
else:
names[tensor] = ng.get_new_name('Const')
return names
def generate_missing_names(self):
name_generator = utils.NameGenerator(used_names=set(
t.name for t in self.tensors if t.name))
for t in self.tensors:
if not t.name:
if t.is_variable:
t.name = name_generator.get_new_name('variable')
elif t.is_constant:
t.name = name_generator.get_new_name('constant')
else:
assert t.producer
t.name = name_generator.get_new_name(t.producer.name)
label_generator = utils.NameGenerator(used_names=set(
op.label for op in self.operations if op.label))
for op in self.operations:
if not op.label:
op.label = label_generator.get_new_name(op.outputs[0].name)
def __init__(self,
enable_default_conversion=False,
custom_converter_by_op_name=None):
converters = {}
converters.update(_StandardConverters)
if custom_converter_by_op_name is not None:
converters.update(custom_converter_by_op_name)
default_op_converter = convert_default if enable_default_conversion else None
super(Converter,
self).__init__(op_converter_by_name=converters,
default_op_converter=default_op_converter)
self.displayed_warnings = set()
self.name_generator = utils.NameGenerator()
def generate_missing_names(self):
# type: (TFGraph)->None
# assert self.is_unique
ng = utils.NameGenerator()
for t in self.tensors:
if t.name and ng.is_available(t.name):
t.name = ng.get_new_name(t.name)
elif t.producer:
t.name = ng.get_new_name(t.producer.name.split('.')[-1])
elif t.is_variable:
t.name = ng.get_new_name("variable")
elif t.is_constant:
t.name = ng.get_new_name("constant")
else:
t.name = ng.get_new_name("placeholder")
def generate_missing_names(self):
# type: ()->None
# assert self.is_unique
ng = utils.NameGenerator(used_names=set(t.name for t in self.tensors if t.name))
for t in self.tensors:
if t.name:
pass
elif self.input_ids is not None and t in self.inputs:
t.name = ng.get_new_name(self.input_ids[list(self.inputs).index(t)])
elif self.output_ids is not None and t in self.outputs:
t.name = ng.get_new_name(self.output_ids[list(self.outputs).index(t)])
elif t.is_variable:
t.name = ng.get_new_name('variable')
elif t.is_constant:
t.name = ng.get_new_name('constant')
elif t.producer is None:
t.name = ng.get_new_name('external')
else:
t.name = ng.get_new_name(t.producer.name.split('.')[-1])