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
|
import argparse
import logging as log
import sys
log.basicConfig(format="[ %(levelname)s ] %(message)s", level=log.INFO, stream=sys.stdout)
import os
import numpy as np
from openvino.inference_engine import IENetwork
def python_api_infer(net, feed_dict, device, lib, api, nireq, outputs_to_add: list = None):
"""
Function to perform IE inference using python API "in place"
:param net: IENetwork instance
:param feed_dict: Dict which contains mapping between input blob and input data
:param device: Device name for inference
:param lib: Absolute path to custom kernel lib
:param outputs_to_add: Layer names list to take output from
:param api: Defines use synchronous infer or asynchronous
:param nireq: Number of infer requests to create for asynchronous infer
:return: Dict containing out blob name and out data
"""
from openvino.inference_engine import IECore
ie = IECore()
if outputs_to_add:
net.add_outputs(outputs_to_add)
exec_net = ie.load_network(net, device, num_requests=nireq)
if api == "async":
res = []
for i in range(nireq):
reqest_handler = exec_net.start_async(request_id=i, inputs=feed_dict)
reqest_handler.wait()
res.append(reqest_handler.outputs)
else:
res = exec_net.infer(inputs=feed_dict)
del net
# It's important to delete executable network first to avoid double free in plugin offloading.
# Issue relates ony for hetero and Myriad plugins
del exec_net
del ie
return res
def cli_parser():
parser = argparse.ArgumentParser(description='Python_api reproducer')
parser.add_argument('-i', dest='feed_dict', required=True, help='Path to input data in .npz format')
parser.add_argument('-m', dest='ir_path', required=True, help='Path to XML file of IR')
parser.add_argument('-d', dest='device', required=True, help='Target device to infer on')
parser.add_argument('-api', dest='api', default='sync', help='')
parser.add_argument('-nireq', dest='nireq', default=1, help='')
parser.add_argument('-r', dest='out_path', default=None,
help='Dumps results to the output folder')
parser.add_argument('--out_layers', dest='out_layers', default=[],
help='Names of layers to dump inference results. Example: "input,conv3d"')
parser.add_argument('--dump_all_layers', dest='dump_all_layers', default=False, action="store_true",
help='Bool value to dump inference results from all layers')
args = parser.parse_args()
feed_dict = args.feed_dict
ir_path = args.ir_path
device = args.device
lib = args.lib
api = args.api
nireq = int(args.nireq)
out_path = args.out_path
if out_path and not os.path.exists(out_path):
os.makedirs(out_path)
out_layers = args.out_layers.split(",") if args.out_layers else args.out_layers
dump_all_layers = args.dump_all_layers
if out_layers and dump_all_layers:
raise AttributeError('CMD arguments "out_layers" and "dump_all_layers" were specified together. '
'Please, specify only one argument')
return feed_dict, ir_path, device, lib, api, nireq, out_path, out_layers, dump_all_layers
if __name__ == "__main__":
feed_dict, ir_path, device, lib, api, nireq, out_path, out_layers, dump_all_layers = cli_parser()
bin_path = os.path.splitext(ir_path)[0] + '.bin'
feed_dict = dict(np.load(feed_dict))
network = IENetwork(model=ir_path, weights=bin_path)
if dump_all_layers:
out_layers = list(network.layers.keys())
results = python_api_infer(net=network, feed_dict=feed_dict, device=device, lib=lib, api=api, nireq=nireq,
outputs_to_add=out_layers)
if out_path:
if api == "async":
for i, result in enumerate(results):
dump_path = os.path.join(out_path, "dump_req{}.npz".format(str(i)))
np.savez(dump_path, **result)
log.info("Path for inference results for {} request: {}".format(str(i), dump_path))
else:
dump_path = os.path.join(out_path, "dump.npz")
np.savez(os.path.join(out_path, "dump.npz"), **results)
log.info("Path for inference results: {}".format(dump_path))
else:
log.info("Inference results won't be saved in the file. "
"To do it need to specify '-r' option.")
log.info("Inference results:")
log.info(results)
log.info("SUCCESS!")
|
