TF-TRT 1.x Workflow With A Frozen Graph

i follow the guide https://docs.nvidia.com/deeplearning/frameworks/tf-trt-user-guide/index.html to use tf_trt with a frozen graph, but i dont know how to implement a project as follows :

import tensorflow as tf
from tensorflow.python.compiler.tensorrt import trt_convert as trt
with tf.Session() as sess:
# First deserialize your frozen graph:
with tf.gfile.GFile(“/path/to/your/frozen/graph.pb”, ‘rb’) as f:
frozen_graph = tf.GraphDef()
frozen_graph.ParseFromString(f.read())
# Now you can create a TensorRT inference graph from your
# frozen graph:
converter = trt.TrtGraphConverter(
input_graph_def=frozen_graph,
nodes_blacklist=['logits', 'classes']) #output nodes
trt_graph = converter.convert()
# Import the TensorRT graph into a new graph and run:
output_node = tf.import_graph_def(
trt_graph,
return_elements=['logits', 'classes'])
sess.run(output_node)

i have some problems :
1, where can i pass input for sess.run(output_node) ?
2, nodes_blacklist’s mean ? how to set ? why has error when i set nodes_blacklist=[’ '] or no set ?
3, is there a complete project used tf_trt with frozen graph ? in this repository, i just get a demo used tf_trt with saved model.
please give me some advise, thank you