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| 1 | +# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. |
| 2 | +# |
| 3 | +# Redistribution and use in source and binary forms, with or without |
| 4 | +# modification, are permitted provided that the following conditions |
| 5 | +# are met: |
| 6 | +# * Redistributions of source code must retain the above copyright |
| 7 | +# notice, this list of conditions and the following disclaimer. |
| 8 | +# * Redistributions in binary form must reproduce the above copyright |
| 9 | +# notice, this list of conditions and the following disclaimer in the |
| 10 | +# documentation and/or other materials provided with the distribution. |
| 11 | +# * Neither the name of NVIDIA CORPORATION nor the names of its |
| 12 | +# contributors may be used to endorse or promote products derived |
| 13 | +# from this software without specific prior written permission. |
| 14 | +# |
| 15 | +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY |
| 16 | +# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| 17 | +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR |
| 18 | +# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR |
| 19 | +# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
| 20 | +# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
| 21 | +# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
| 22 | +# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY |
| 23 | +# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
| 24 | +# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
| 25 | +# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| 26 | + |
| 27 | +import triton_python_backend_utils as pb_utils |
| 28 | +import time |
| 29 | +import numpy as np |
| 30 | + |
| 31 | +class TritonPythonModel: |
| 32 | + def initialize(self, args): |
| 33 | + pass |
| 34 | + |
| 35 | + def execute(self, requests): |
| 36 | + pass |
| 37 | + |
| 38 | + def finalize(self): |
| 39 | + print('Cleaning up...') |
| 40 | + input0_np = np.random.randint(3, size=1, dtype=np.int32) |
| 41 | + input0 = pb_utils.Tensor('IN', input0_np) |
| 42 | + infer_request = pb_utils.InferenceRequest(model_name='square_int32', |
| 43 | + inputs=[input0], |
| 44 | + requested_output_names=['OUT']) |
| 45 | + infer_responses = infer_request.exec(decoupled=True) |
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