Conversion from Tensorflow to TensorRT

import tensorflow as tf

import tensorflow.contrib.tensorrt as trt

# Inference with TF-TRT frozen graph workflow:

graph = tf.Graph()

with graph.as_default():

with tf.Session() as sess:

# First deserialize your frozen graph:

with tf.gfile.GFile(“frozen_inference_graph.pb”, ‘rb’) as f:

graph_def = tf.GraphDef()

graph_def.ParseFromString(f.read())

# Now you can create a TensorRT inference graph from your

# frozen graph:

trt_graph = trt.create_inference_graph(

input_graph_def=graph_def,

outputs=[“output_list”],

max_batch_size=1,

max_workspace_size_bytes=2000,

precision_mode=“FP16”)

# Import the TensorRT graph into a new graph and run:

output_node = tf.import_graph_def(

trt_graph,

return_elements=[“output”])

sess.run(output_node)

I am using tensorflow ssd mobilenet model. Can i know what outputs list parameter i should use.