吳裕雄 python 神經網絡——TensorFlow pb文件保存方法
阿新 • • 發佈:2019-05-16
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import tensorflow as tf from tensorflow.python.framework import graph_util v1 = tf.Variable(tf.constant(1.0, shape=[1]), name = "v1") v2 = tf.Variable(tf.constant(2.0, shape=[1]), name = "v2") result = v1 + v2 init_op = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init_op) graph_def= tf.get_default_graph().as_graph_def() output_graph_def = graph_util.convert_variables_to_constants(sess, graph_def, [‘add‘]) with tf.gfile.GFile("E:\\Saved_model\\combined_model.pb", "wb") as f: f.write(output_graph_def.SerializeToString())
from tensorflow.python.platform importgfile with tf.Session() as sess: model_filename = "E:\\Saved_model\\combined_model.pb" with gfile.FastGFile(model_filename, ‘rb‘) as f: graph_def = tf.GraphDef() graph_def.ParseFromString(f.read()) result = tf.import_graph_def(graph_def, return_elements=["add:0"]) print(sess.run(result))
吳裕雄 python 神經網絡——TensorFlow pb文件保存方法