def function_to_wrap(*args): # pylint: disable=missing-docstring
if len(args) != len(input_tensor_names):
raise RuntimeError('Expected {} arguments, found {}.'.format(
str(len(input_tensor_names)), str(len(args))))
graph_def = serialization_utils.unpack_graph_def(comp.tensorflow.graph_def)
init_op = comp.tensorflow.initialize_op
if init_op:
graph_def = graph_utils.add_control_deps_for_init_op(graph_def, init_op)
return tf.import_graph_def(
graph_merge.uniquify_shared_names(graph_def),
input_map=dict(zip(input_tensor_names, args)),
return_elements=output_tensor_names)
def function_to_wrap(*args): # pylint: disable=missing-docstring
if len(args) != len(input_tensor_names):
raise RuntimeError('Expected {} arguments, found {}.'.format(
str(len(input_tensor_names)), str(len(args))))
graph_def = serialization_utils.unpack_graph_def(
comp.tensorflow.graph_def)
init_op = comp.tensorflow.initialize_op
init_names = [init_op] if init_op else []
returned_elements = tf.import_graph_def(
graph_merge.uniquify_shared_names(graph_def),
input_map=dict(zip(input_tensor_names, args)),
return_elements=output_tensor_names + init_names)
if init_names:
with tf.control_dependencies([returned_elements[-1]]):
return [tf.identity(x) for x in returned_elements[0:-1]]
else:
return returned_elements
def _import_fn():
return tf.import_graph_def(
graph_merge.uniquify_shared_names(graph_def), name='')
def _import_fn():
return tf.import_graph_def(
graph_merge.uniquify_shared_names(graph_def),
input_map=dict(list(zip(input_tensor_names, args))),
return_elements=output_tensor_names)
