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Add test for delayed model startups in PB (triton-inference-server#3095)
* Add test for delayed model startups in PB * Review edits
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# Copyright 2021, 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. | ||
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name: "delayed_model" | ||
backend: "python" | ||
max_batch_size: 64 | ||
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input [ | ||
{ | ||
name: "IN" | ||
data_type: TYPE_FP32 | ||
dims: [ -1 ] | ||
} | ||
] | ||
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output [ | ||
{ | ||
name: "OUT" | ||
data_type: TYPE_FP32 | ||
dims: [ -1 ] | ||
} | ||
] | ||
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instance_group [ | ||
{ | ||
count: 1 | ||
kind : KIND_CPU | ||
} | ||
] |
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# Copyright 2021, 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. | ||
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import triton_python_backend_utils as pb_utils | ||
import time | ||
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# Sleep for 5 seconds to ensure that delayed startup works properly. | ||
time.sleep(5) | ||
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class TritonPythonModel: | ||
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def execute(self, requests): | ||
responses = [] | ||
for request in requests: | ||
input_tensor = pb_utils.get_input_tensor_by_name(request, "IN") | ||
out_tensor = utils.Tensor("OUT", input_tensor.as_numpy()) | ||
responses.append(utils.InferenceResponse([out_tensor])) | ||
return responses | ||
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def finalize(self): | ||
pass |