mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
75 lines
3.6 KiB
C++
75 lines
3.6 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 "buffers.h"
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#include "tensorrt_llm/batch_manager/decoderBuffers.h"
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#include "tensorrt_llm/nanobind/batch_manager/llmRequest.h"
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#include "tensorrt_llm/nanobind/common/customCasters.h"
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#include "tensorrt_llm/runtime/torch.h"
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#include <ATen/ATen.h>
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#include <nanobind/nanobind.h>
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#include <nanobind/operators.h>
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#include <torch/extension.h>
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namespace nb = nanobind;
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namespace tb = tensorrt_llm::batch_manager;
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namespace tr = tensorrt_llm::runtime;
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using tr::SizeType32;
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namespace tensorrt_llm::nanobind::batch_manager
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{
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void Buffers::initBindings(nb::module_& m)
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{
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nb::class_<tb::DecoderInputBuffers>(m, "DecoderInputBuffers")
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.def(nb::init<runtime::SizeType32, runtime::SizeType32, tr::BufferManager>(), nb::arg("max_batch_size"),
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nb::arg("max_tokens_per_engine_step"), nb::arg("manager"))
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.def_rw("setup_batch_slots", &tb::DecoderInputBuffers::setupBatchSlots)
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.def_rw("setup_batch_slots_device", &tb::DecoderInputBuffers::setupBatchSlotsDevice)
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.def_rw("fill_values", &tb::DecoderInputBuffers::fillValues)
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.def_rw("fill_values_device", &tb::DecoderInputBuffers::fillValuesDevice)
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.def_rw("inputs_ids", &tb::DecoderInputBuffers::inputsIds)
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.def_rw("forward_batch_slots", &tb::DecoderInputBuffers::forwardBatchSlots)
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.def_rw("decoder_logits", &tb::DecoderInputBuffers::decoderLogits)
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.def_rw("decoder_requests", &tb::DecoderInputBuffers::decoderRequests);
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nb::class_<tb::DecoderOutputBuffers>(m, "DecoderOutputBuffers")
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.def_rw("sequence_lengths_host", &tb::DecoderOutputBuffers::sequenceLengthsHost)
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.def_rw("finished_sum_host", &tb::DecoderOutputBuffers::finishedSumHost)
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.def_prop_ro("new_output_tokens_host",
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[](tb::DecoderOutputBuffers& self) { return tr::Torch::tensor(self.newOutputTokensHost); })
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.def_rw("cum_log_probs_host", &tb::DecoderOutputBuffers::cumLogProbsHost)
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.def_rw("log_probs_host", &tb::DecoderOutputBuffers::logProbsHost)
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.def_rw("finish_reasons_host", &tb::DecoderOutputBuffers::finishReasonsHost);
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nb::class_<tb::SlotDecoderBuffers>(m, "SlotDecoderBuffers")
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.def(nb::init<runtime::SizeType32, runtime::SizeType32, runtime::BufferManager const&>(),
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nb::arg("max_beam_width"), nb::arg("max_seq_len"), nb::arg("buffer_manager"))
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.def_rw("output_ids", &tb::SlotDecoderBuffers::outputIds)
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.def_rw("output_ids_host", &tb::SlotDecoderBuffers::outputIdsHost)
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.def_rw("sequence_lengths_host", &tb::SlotDecoderBuffers::sequenceLengthsHost)
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.def_rw("cum_log_probs", &tb::SlotDecoderBuffers::cumLogProbs)
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.def_rw("cum_log_probs_host", &tb::SlotDecoderBuffers::cumLogProbsHost)
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.def_rw("log_probs", &tb::SlotDecoderBuffers::logProbs)
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.def_rw("log_probs_host", &tb::SlotDecoderBuffers::logProbsHost)
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.def_rw("finish_reasons_host", &tb::SlotDecoderBuffers::finishReasonsHost);
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}
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} // namespace tensorrt_llm::nanobind::batch_manager
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