TensorRT-LLMs/cpp/tensorrt_llm/nanobind/testing/modelSpecBinding.cpp
Linda 3efad2e58c
feat: nanobind bindings (#6185)
Signed-off-by: Linda-Stadter <57756729+Linda-Stadter@users.noreply.github.com>
2025-07-21 08:56:57 +01:00

88 lines
5.2 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2023-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "modelSpecBinding.h"
#include "tensorrt_llm/nanobind/common/customCasters.h"
#include "tensorrt_llm/testing/modelSpec.h"
#include <nanobind/nanobind.h>
namespace nb = nanobind;
using tensorrt_llm::testing::ModelSpec;
using tensorrt_llm::testing::KVCacheType;
using tensorrt_llm::testing::QuantMethod;
using tensorrt_llm::testing::OutputContentType;
namespace tensorrt_llm::nanobind::testing
{
void initBindings(nb::module_& m)
{
nb::enum_<QuantMethod>(m, "QuantMethod", nb::is_arithmetic(), "Quantization Method")
.value("NONE", QuantMethod::kNONE, "No Quantization")
.value("SMOOTH_QUANT", QuantMethod::kSMOOTH_QUANT, "Smooth Quantization");
nb::enum_<OutputContentType>(m, "OutputContentType", nb::is_arithmetic(), "Output Content Type")
.value("NONE", OutputContentType::kNONE, "No Output Content")
.value("CONTEXT_LOGITS", OutputContentType::kCONTEXT_LOGITS, "Context Logits")
.value("GENERATION_LOGITS", OutputContentType::kGENERATION_LOGITS, "Generation Logits")
.value("LOG_PROBS", OutputContentType::kLOG_PROBS, "Log Probs")
.value("CUM_LOG_PROBS", OutputContentType::kCUM_LOG_PROBS, "Cumulative Log");
nb::class_<ModelSpec>(m, "ModelSpec")
.def(nb::init<std::string const&, nvinfer1::DataType>())
.def("use_gpt_plugin", &ModelSpec::useGptAttentionPlugin, nb::rv_policy::reference_internal)
.def("use_packed_input", &ModelSpec::usePackedInput, nb::rv_policy::reference_internal)
.def("set_kv_cache_type", &ModelSpec::setKVCacheType, nb::rv_policy::reference_internal)
.def("use_decoder_per_request", &ModelSpec::useDecoderPerRequest, nb::rv_policy::reference_internal)
.def("use_tensor_parallelism", &ModelSpec::useTensorParallelism, nb::rv_policy::reference_internal)
.def("use_pipeline_parallelism", &ModelSpec::usePipelineParallelism, nb::rv_policy::reference_internal)
.def("use_context_parallelism", &ModelSpec::useContextParallelism, nb::rv_policy::reference_internal)
.def("set_draft_tokens", &ModelSpec::setDraftTokens, nb::rv_policy::reference_internal)
.def("use_accept_by_logits", &ModelSpec::useAcceptByLogits, nb::rv_policy::reference_internal)
.def("use_mamba_plugin", &ModelSpec::useMambaPlugin, nb::rv_policy::reference_internal)
.def("gather_logits", &ModelSpec::gatherLogits, nb::rv_policy::reference_internal)
.def("replace_logits", &ModelSpec::replaceLogits, nb::rv_policy::reference_internal)
.def("return_log_probs", &ModelSpec::returnLogProbs, nb::rv_policy::reference_internal)
.def("smoke_test", &ModelSpec::smokeTest, nb::rv_policy::reference_internal)
.def("use_medusa", &ModelSpec::useMedusa, nb::rv_policy::reference_internal)
.def("use_eagle", &ModelSpec::useEagle, nb::rv_policy::reference_internal)
.def("use_lookahead_decoding", &ModelSpec::useLookaheadDecoding, nb::rv_policy::reference_internal)
.def("use_explicit_draft_tokens_decoding", &ModelSpec::useExplicitDraftTokensDecoding,
nb::rv_policy::reference_internal)
.def("use_draft_tokens_external_decoding", &ModelSpec::useDraftTokensExternalDecoding,
nb::rv_policy::reference_internal)
.def("use_logits", &ModelSpec::useLogits)
.def("use_multiple_profiles", &ModelSpec::useMultipleProfiles, nb::rv_policy::reference_internal)
.def("set_max_input_length", &ModelSpec::setMaxInputLength, nb::rv_policy::reference_internal)
.def("set_max_output_length", &ModelSpec::setMaxOutputLength, nb::rv_policy::reference_internal)
.def("set_quant_method", &ModelSpec::setQuantMethod, nb::rv_policy::reference_internal)
.def("use_lora_plugin", &ModelSpec::useLoraPlugin, nb::rv_policy::reference_internal)
.def("get_input_file", &ModelSpec::getInputFile)
.def("get_model_path", &ModelSpec::getModelPath)
.def("get_results_file", &ModelSpec::getResultsFile)
.def("get_generation_logits_file", &ModelSpec::getGenerationLogitsFile)
.def("get_context_logits_file", &ModelSpec::getContextLogitsFile)
.def("get_cum_log_probs_file", &ModelSpec::getCumLogProbsFile)
.def("get_log_probs_file", &ModelSpec::getLogProbsFile)
.def("enable_context_fmha_fp32_acc", &ModelSpec::enableContextFMHAFp32Acc, nb::rv_policy::reference_internal)
.def("get_enable_context_fmha_fp32_acc", &ModelSpec::getEnableContextFMHAFp32Acc)
.def("__copy__", [](ModelSpec const& self) { return ModelSpec(self); });
}
} // namespace tensorrt_llm::nanobind::testing