identity.py 2.2 KB
Newer Older
Neelay Shah's avatar
Neelay Shah committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
# SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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.


import numpy
18

Neelay Shah's avatar
Neelay Shah committed
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
from triton_distributed.worker import Operator, RemoteInferenceRequest


class Identity(Operator):
    """
    This is a dummy workflow that sends a single input as an output.
    """

    def __init__(
        self,
        name,
        version,
        triton_core,
        request_plane,
        data_plane,
        params,
        repository,
        logger,
    ):
        self._triton_core = triton_core
        self._request_plane = request_plane
        self._data_plane = data_plane
        self._params = params

    async def execute(self, requests: list[RemoteInferenceRequest]):
        for request in requests:
            try:
                array = numpy.from_dlpack(request.inputs["input"])
            except Exception as e:
                print(e)
                await request.response_sender().send(final=True, error=e)
                return

            outputs: dict[str, numpy.ndarray] = {"output": array}

            store_outputs_in_response = False

            if "store_outputs_in_response" in self._params:
                store_outputs_in_response = self._params["store_outputs_in_response"]

            store_outputs_in_response_set = set()

            if store_outputs_in_response:
                store_outputs_in_response_set.add("output")

            await request.response_sender().send(
                outputs=outputs,
                final=True,
                store_outputs_in_response=store_outputs_in_response_set,
            )
            for output in outputs.values():
                del output