-
Notifications
You must be signed in to change notification settings - Fork 1
/
fold_constants.py
59 lines (51 loc) · 2.62 KB
/
fold_constants.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
#!/usr/bin/env python3
# Copyright 2020 NVIDIA Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
from tensorflow.core.protobuf import config_pb2, rewriter_config_pb2, meta_graph_pb2
from tensorflow.core.framework import graph_pb2
from tensorflow.python.framework import importer, ops
from tensorflow.python.grappler import tf_optimizer
from tensorflow.python.training import saver
def constfold(graphdef, output_name):
graph = ops.Graph()
with graph.as_default():
outputs = output_name.split(',')
output_collection = meta_graph_pb2.CollectionDef()
output_list = output_collection.node_list.value
for output in outputs:
output_list.append(output)
print(graph)
importer.import_graph_def(graphdef, name="")
metagraph = saver.export_meta_graph(graph_def=graph.as_graph_def(add_shapes=True), graph=graph)
metagraph.collection_def["train_op"].CopyFrom(output_collection)
rewriter_config = rewriter_config_pb2.RewriterConfig()
rewriter_config.optimizers.extend(["constfold"])
rewriter_config.meta_optimizer_iterations = (rewriter_config_pb2.RewriterConfig.ONE)
session_config = config_pb2.ConfigProto()
session_config.graph_options.rewrite_options.CopyFrom(rewriter_config)
return tf_optimizer.OptimizeGraph(session_config, metagraph)
if __name__ == '__main__':
parser = argparse.ArgumentParser("Folds constants in the provided frozen model")
parser.add_argument("-i", "--input", help="The input frozen model to be constant folded.")
parser.add_argument("--output_node", default="softmax_1", help="Output node names separated by commas")
parser.add_argument("-o", "--output", default="saved_results/folded_mnist.pb", help="Path to constant folded output graph")
args, _ = parser.parse_known_args()
with open(args.input, 'rb') as f:
graphdef = graph_pb2.GraphDef()
graphdef.ParseFromString(f.read())
folded_graph = constfold(graphdef, args.output_node)
print("Writing output to {:}".format(args.output))
with open(args.output, "wb") as f:
f.write(folded_graph.SerializeToString())