mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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116 lines
4.6 KiB
Python
116 lines
4.6 KiB
Python
#!/usr/bin/env python
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# Copyright 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions
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# are met:
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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# * Neither the name of NVIDIA CORPORATION nor the names of its
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# contributors may be used to endorse or promote products derived
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# from this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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import os
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import sys
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from functools import partial
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import numpy as np
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from tritonclient import grpc as grpcclient
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from tritonclient.utils import InferenceServerException
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sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
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from llmapi_client import (UserData, _prepare_inputs, callback,
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prepare_stop_signals)
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if __name__ == "__main__":
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input_data = np.array([
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"The current time is",
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], dtype=object)
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output_len = 100
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inputs = _prepare_inputs(input_data, output_len)
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stop_inputs = prepare_stop_signals()
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request_id = 1
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user_data = UserData()
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with grpcclient.InferenceServerClient(
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url="localhost:8001",
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verbose=False,
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ssl=False,
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root_certificates=None,
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private_key=None,
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certificate_chain=None,
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) as triton_client:
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# Send stop request for non-existing request
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triton_client.async_infer(
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"tensorrt_llm",
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stop_inputs,
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request_id=str(request_id), # Request does not exist yet
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callback=partial(callback, user_data),
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parameters={'Streaming': False})
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result = user_data._completed_requests.get()
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assert isinstance(result, InferenceServerException)
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assert result.status() == "StatusCode.CANCELLED"
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# Send actual request
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infer_response = triton_client.async_infer(
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"tensorrt_llm",
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inputs,
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request_id=str(request_id),
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callback=partial(callback, user_data),
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parameters={'Streaming': False})
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result = user_data._completed_requests.get()
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print(
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f'Output text: {result.as_numpy("text_output")[0].decode("utf-8")}')
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# Cancel request after it is completed
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infer_response.cancel()
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# Send stop request for completed request
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triton_client.async_infer("tensorrt_llm",
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stop_inputs,
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request_id=str(request_id),
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callback=partial(callback, user_data),
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parameters={'Streaming': False})
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cancel_result = user_data._completed_requests.get()
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assert isinstance(cancel_result, InferenceServerException)
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assert cancel_result.status() == "StatusCode.CANCELLED"
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# Send a second request to check if server is still healthy
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infer_response_2 = triton_client.async_infer(
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"tensorrt_llm",
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inputs,
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request_id=str(request_id + 1),
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callback=partial(callback, user_data),
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parameters={'Streaming': False})
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# Get result of second request
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result_2 = user_data._completed_requests.get()
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print('Got completed request')
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print(
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f'Output text: {result_2.as_numpy("text_output")[0].decode("utf-8")}'
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)
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# Check that both results match
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assert np.array_equal(result.as_numpy("text_output"),
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result_2.as_numpy("text_output"))
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