-
Notifications
You must be signed in to change notification settings - Fork 152
/
client.py
83 lines (72 loc) · 3.55 KB
/
client.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
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
# Copyright 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import sys
import numpy as np
import tritonclient.http as httpclient
from tritonclient.utils import *
nobatch_model_name = "nobatch_auto_complete"
batch_model_name = "batch_auto_complete"
def validate_ios(config, expected_ios, model_name):
for io in config:
for expected_io in expected_ios:
if io["name"] == expected_io["name"]:
if io["data_type"] != expected_io["data_type"]:
print("model '" + model_name + "' has unexpected data_type")
sys.exit(1)
elif io["dims"] != expected_io["dims"]:
print("model '" + model_name + "' has unexpected dims")
sys.exit(1)
if __name__ == "__main__":
with httpclient.InferenceServerClient("localhost:8000") as client:
expected_max_batch_size = {
"nobatch_auto_complete": 0,
"batch_auto_complete": 4,
}
expected_inputs = [
{"name": "INPUT0", "data_type": "TYPE_FP32", "dims": [4]},
{"name": "INPUT1", "data_type": "TYPE_FP32", "dims": [4]},
]
expected_outputs = [
{"name": "OUTPUT0", "data_type": "TYPE_FP32", "dims": [4]},
{"name": "OUTPUT1", "data_type": "TYPE_FP32", "dims": [4]},
]
models = [nobatch_model_name, batch_model_name]
for model_name in models:
# Validate the auto-complete model configuration
model_config = client.get_model_config(model_name)
if model_config["max_batch_size"] != expected_max_batch_size[model_name]:
print("model '" + model_name + "' has unexpected max_batch_size")
sys.exit(1)
validate_ios(model_config["input"], expected_inputs, model_name)
validate_ios(model_config["output"], expected_outputs, model_name)
print(
"'"
+ model_name
+ "' configuration matches the expected "
+ "auto complete configuration\n"
)
print("PASS: auto_complete")
sys.exit(0)