Let us first load the graph from .pb
file.
import tensorflow as tf
from tensorflow.python.platform import gfile
GRAPH_PB_PATH = './model/tensorflow_inception_v3_stripped_optimized_quantized.pb' #path to your .pb file
with tf.Session(config=config) as sess:
print("load graph")
with gfile.FastGFile(GRAPH_PB_PATH,'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
sess.graph.as_default()
tf.import_graph_def(graph_def, name='')
graph_nodes=[n for n in graph_def.node]
Now when you freeze a graph to .pb
file your variables are converted to Const
type and the weights which were trainabe variables would also be stored as Const
in .pb
file. graph_nodes
contains all the nodes in graph. But we are interested in all the Const
type nodes.
wts = [n for n in graph_nodes if n.op=='Const']
Each element of wts
is of NodeDef type. It has several atributes such as name, op etc. The values can be extracted as follows -
from tensorflow.python.framework import tensor_util
for n in wts:
print "Name of the node - %s" % n.name
print "Value - "
print tensor_util.MakeNdarray(n.attr['value'].tensor)
Hope this solves your concern.
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