Created
April 24, 2018 02:55
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import tensorflow as tf | |
def load_graph(frozen_graph_filename): | |
# We load the protobuf file from the disk and parse it to retrieve the | |
# unserialized graph_def | |
with tf.gfile.GFile(frozen_graph_filename, "rb") as f: | |
graph_def = tf.GraphDef() | |
graph_def.ParseFromString(f.read()) | |
# Then, we import the graph_def into a new Graph and returns it | |
with tf.Graph().as_default() as graph: | |
# The name var will prefix every op/nodes in your graph | |
# Since we load everything in a new graph, this is not needed | |
tf.import_graph_def(graph_def, name="prefix") | |
return graph | |
graph=load_graph('bcdf_emotions.pb') | |
for op in graph.get_operations(): | |
print(op.name) | |
x = graph.get_tensor_by_name('prefix/dense_4_input:0') | |
y = graph.get_tensor_by_name('prefix/output_node0:0') | |
i=np.random.rand(136) | |
with tf.Session(graph=graph) as sess: | |
y_out=sess.run(y,feed_dict={x:[i]}) | |
print(y_out) |
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