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
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
r"""Replaces a subgraph of a TensorFlow GraphDef with a single node.
In conjunction with TOCO's --allow_custom_op this script allows selected
portions of a TensorFlow GraphDef to be executed by custom code.
Example:
bazel run tensorflow/contrib/lite/python:create_custom_op -- \
--input_graph=/tmp/input.pb \
--output_graph=/tmp/output.pb \
--inputs=concat,concat_1 \
--outputs=detection_classes \
--op_definition='op:"PostProcessing" attr{key:"num" value:{i:10}}'
The above will identify a subgraph starting at nodes 'concat' and 'concat_1',
and ending at 'detection_classes'. All nodes in between will be removed and
replaced by a new op called 'PostProcessing'.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import uuid as _uuid
from absl import app
from absl import flags
from google.protobuf import text_format
from tensorflow.contrib.framework.python.framework.graph_util import fuse_op
from tensorflow.core.framework import graph_pb2
from tensorflow.core.framework import node_def_pb2
from tensorflow.core.framework import types_pb2
from tensorflow.python.platform import gfile
FLAGS = flags.FLAGS
flags.DEFINE_string("input_graph", "", "Binary graphdef to load.")
flags.DEFINE_string("output_graph", "", "Resulting binary graphdef.")
flags.DEFINE_string("inputs", "",
"Comma-separated list of inputs to the subgraph.")
flags.DEFINE_string("outputs", "",
"Comma-separated list of outputs of the subgraph.")
flags.DEFINE_string("op_definition", "",
"A text NodeDef defining the contents of the custom op.")
def _read_graph_def(filename):
if not gfile.Exists(filename):
raise ValueError("Input graph file '" + filename + "' does not exist!")
graph_def = graph_pb2.GraphDef()
with gfile.FastGFile(filename, "rb") as f:
graph_def.ParseFromString(f.read())
return graph_def
def _write_graph_def(graph_def, filename):
if not filename:
raise ValueError("Output graph file not specified")
with gfile.Open(filename, "wb") as f:
f.write(graph_def.SerializeToString())
def _collapse_subgraph(graph_def, inputs, outputs, op_definition):
"""Substitute a custom op for the subgraph delimited by inputs and outputs."""
name = _uuid.uuid1().hex
# We need a default type, but it can be changed using 'op_definition'.
default_type = types_pb2.DT_FLOAT
new_graph = fuse_op(
graph_def=graph_def,
input_nodes=inputs,
output_nodes=outputs,
output_dtypes=[default_type for _ in outputs],
output_quantized=False,
op_name=name,
op_type="CustomTfLiteOp")
node_def = node_def_pb2.NodeDef()
text_format.Parse(op_definition, node_def)
for node in new_graph.node:
if node.name == name:
node.MergeFrom(node_def)
return new_graph
def main(argv):
del argv # unused
graph = _read_graph_def(filename=flags.FLAGS.input_graph)
graph = _collapse_subgraph(
graph_def=graph,
inputs=flags.FLAGS.inputs.split(","),
outputs=flags.FLAGS.outputs.split(","),
op_definition=flags.FLAGS.op_definition)
_write_graph_def(graph_def=graph, filename=flags.FLAGS.output_graph)
if __name__ == "__main__":
app.run(main)
|
