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8681b3a4c0
* Update TensorRT-LLM --------- Co-authored-by: Bhuvanesh Sridharan <bhuvanesh.sridharan@sprinklr.com> Co-authored-by: Qingquan Song <ustcsqq@gmail.com>
42 lines
1.6 KiB
C++
42 lines
1.6 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "bindings.h"
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#include "tensorrt_llm/batch_manager/common.h"
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#include "tensorrt_llm/batch_manager/microBatchScheduler.h"
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#include "tensorrt_llm/pybind/utils/bindTypes.h"
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namespace py = pybind11;
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namespace tb = tensorrt_llm::batch_manager;
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namespace tle = tensorrt_llm::executor;
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using namespace tensorrt_llm::runtime;
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namespace tensorrt_llm::pybind::batch_manager
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{
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void initBindings(pybind11::module_& m)
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{
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py::class_<tb::batch_scheduler::ContextChunkingConfig>(m, "ContextChunkingConfig")
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.def(py::init<tle::ContextChunkingPolicy, tensorrt_llm::runtime::SizeType32>(), py::arg("chunking_policy"),
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py::arg("chunk_unit_size"))
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.def_readwrite("chunking_policy", &tb::batch_scheduler::ContextChunkingConfig::chunkingPolicy)
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.def_readwrite("chunk_unit_size", &tb::batch_scheduler::ContextChunkingConfig::chunkUnitSize);
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}
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} // namespace tensorrt_llm::pybind::batch_manager
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