tritonserver-rs 0.4.1

Pefrorm easy and efficient ML models inference
Documentation 
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

# Copyright 2023-2024, 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.

"""Triton Inference Server In-Process Python API

The Triton Inference Server In-Process Python API enables developers to easily
embed a Triton inference server within their python
application. Developers can load and interact with models, send
inference requests, query metrics, etc. Everything available through
the C API for emebedding a Triton Inference Server in C / C++
applications has been provided within a Python API.

Note: The Python API is currently in BETA and interfaces and
capabilities are subject to change. Any feedback is welcome.

Note: Any objects not explicitly exported here are considered private.
Note: Any methods, properties, or arguments prefixed with `_` are
considered private.

"""

from importlib.metadata import PackageNotFoundError, version

from tritonserver._api._allocators import MemoryAllocator as MemoryAllocator
from tritonserver._api._allocators import MemoryBuffer as MemoryBuffer
from tritonserver._api._allocators import MemoryType as MemoryType
from tritonserver._api._allocators import (
    default_memory_allocators as default_memory_allocators,
)
from tritonserver._api._dlpack import DLDeviceType as DLDeviceType
from tritonserver._api._model import Model as Model
from tritonserver._api._model import ModelBatchFlag as ModelBatchFlag
from tritonserver._api._model import ModelTxnPropertyFlag as ModelTxnPropertyFlag
from tritonserver._api._request import InferenceRequest as InferenceRequest
from tritonserver._api._server import InstanceGroupKind as InstanceGroupKind
from tritonserver._api._server import LogFormat as LogFormat
from tritonserver._api._server import Metric as Metric
from tritonserver._api._server import MetricFamily as MetricFamily
from tritonserver._api._server import MetricFormat as MetricFormat
from tritonserver._api._server import MetricKind as MetricKind
from tritonserver._api._server import ModelControlMode as ModelControlMode
from tritonserver._api._server import Options as Options
from tritonserver._api._server import RateLimiterResource as RateLimiterResource
from tritonserver._api._server import RateLimitMode as RateLimitMode
from tritonserver._api._server import Server as Server
from tritonserver._api._tensor import DataType as DataType
from tritonserver._api._tensor import Tensor as Tensor
from tritonserver._c import AlreadyExistsError as AlreadyExistsError
from tritonserver._c import InternalError as InternalError
from tritonserver._c import InvalidArgumentError as InvalidArgumentError
from tritonserver._c import NotFoundError as NotFoundError
from tritonserver._c import TritonError as TritonError
from tritonserver._c import UnavailableError as UnavailableError
from tritonserver._c import UnknownError as UnknownError
from tritonserver._c import UnsupportedError as UnsupportedError

_exceptions = [
    TritonError,
    NotFoundError,
    UnknownError,
    InternalError,
    InvalidArgumentError,
    UnavailableError,
    AlreadyExistsError,
    UnsupportedError,
]


# Rename module for exceptions to simplify stack trace
for exception in _exceptions:
    exception.__module__ = "tritonserver"
    globals()[exception.__name__] = exception

__all__ = []
__version__ = "UNKNOWN"

try:
    __version__ = version("tritonserver")
except PackageNotFoundError:
    pass

del _exceptions
del version
del PackageNotFoundError