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
|
# SPDX-FileCopyrightText: Copyright 2023, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Extract module."""
# pylint: disable=too-many-arguments, too-many-locals
import os
import tensorflow as tf
from tensorflow.lite.python.schema_py_generated import SubGraphT
from mlia.nn.rewrite.core.graph_edit.cut import cut_model
from mlia.nn.rewrite.core.graph_edit.record import record_model
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
def extract(
output_path: str,
model_file: str,
input_filename: str,
input_names: list,
output_names: list,
subgraph: SubGraphT = 0,
skip_outputs: bool = False,
show_progress: bool = False,
num_procs: int = 1,
num_threads: int = 0,
) -> None:
"""Extract a model after cut and record."""
try:
os.mkdir(output_path)
except FileExistsError:
pass
start_file = os.path.join(output_path, "start.tflite")
cut_model(
model_file,
input_names=None,
output_names=input_names,
subgraph_index=subgraph,
output_file=start_file,
)
input_tfrec = os.path.join(output_path, "input.tfrec")
record_model(
input_filename,
start_file,
input_tfrec,
show_progress=show_progress,
num_procs=num_procs,
num_threads=num_threads,
)
replace_file = os.path.join(output_path, "replace.tflite")
cut_model(
model_file,
input_names=input_names,
output_names=output_names,
subgraph_index=subgraph,
output_file=replace_file,
)
end_file = os.path.join(output_path, "end.tflite")
cut_model(
model_file,
input_names=output_names,
output_names=None,
subgraph_index=subgraph,
output_file=end_file,
)
if not skip_outputs:
output_tfrec = os.path.join(output_path, "output.tfrec")
record_model(
input_tfrec,
replace_file,
output_tfrec,
show_progress=show_progress,
num_procs=num_procs,
num_threads=num_threads,
)
end_tfrec = os.path.join(output_path, "end.tfrec")
record_model(
output_tfrec,
end_file,
end_tfrec,
show_progress=show_progress,
num_procs=num_procs,
num_threads=num_threads,
)
|
