I using the below script to convert my frozen_inference_graph into a TensorRT optimized one:
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('frozen_inference_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=['outputs/Softmax']) #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=['outputs/Softmax']) sess.run(output_node) My question is how can I save this optimized graph to disk so I can use it to run inference?
