mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
403370af62
* refactor: Move ModelSpec from tests to core library Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * refactor: Move ModelSpec from runtime to separatedir Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * refactor: Use new bindings path and clean up Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * chore: Updated licenses Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * chore: Remove script_dir from path Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> --------- Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
87 lines
4.3 KiB
C++
87 lines
4.3 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/testing/modelSpec.h"
|
|
|
|
#include <pybind11/pybind11.h>
|
|
#include <pybind11/stl.h>
|
|
|
|
namespace py = pybind11;
|
|
using tensorrt_llm::testing::ModelSpec;
|
|
using tensorrt_llm::testing::KVCacheType;
|
|
using tensorrt_llm::testing::QuantMethod;
|
|
using tensorrt_llm::testing::OutputContentType;
|
|
|
|
namespace tensorrt_llm::pybind::testing
|
|
{
|
|
|
|
void initBindings(py::module_& m)
|
|
{
|
|
py::enum_<QuantMethod>(m, "QuantMethod", py::arithmetic(), "Quantization Method")
|
|
.value("NONE", QuantMethod::kNONE, "No Quantization")
|
|
.value("SMOOTH_QUANT", QuantMethod::kSMOOTH_QUANT, "Smooth Quantization");
|
|
|
|
py::enum_<OutputContentType>(m, "OutputContentType", py::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");
|
|
|
|
py::class_<ModelSpec>(m, "ModelSpec")
|
|
.def(py::init<std::string const&, nvinfer1::DataType>())
|
|
.def("use_gpt_plugin", &ModelSpec::useGptAttentionPlugin)
|
|
.def("use_packed_input", &ModelSpec::usePackedInput)
|
|
.def("set_kv_cache_type", &ModelSpec::setKVCacheType)
|
|
.def("use_decoder_per_request", &ModelSpec::useDecoderPerRequest)
|
|
.def("use_tensor_parallelism", &ModelSpec::useTensorParallelism)
|
|
.def("use_pipeline_parallelism", &ModelSpec::usePipelineParallelism)
|
|
.def("use_context_parallelism", &ModelSpec::useContextParallelism)
|
|
.def("set_draft_tokens", &ModelSpec::setDraftTokens)
|
|
.def("use_accept_by_logits", &ModelSpec::useAcceptByLogits)
|
|
.def("use_mamba_plugin", &ModelSpec::useMambaPlugin)
|
|
.def("gather_logits", &ModelSpec::gatherLogits)
|
|
.def("replace_logits", &ModelSpec::replaceLogits)
|
|
.def("return_log_probs", &ModelSpec::returnLogProbs)
|
|
.def("smoke_test", &ModelSpec::smokeTest)
|
|
.def("use_medusa", &ModelSpec::useMedusa)
|
|
.def("use_eagle", &ModelSpec::useEagle)
|
|
.def("use_lookahead_decoding", &ModelSpec::useLookaheadDecoding)
|
|
.def("use_explicit_draft_tokens_decoding", &ModelSpec::useExplicitDraftTokensDecoding)
|
|
.def("use_draft_tokens_external_decoding", &ModelSpec::useDraftTokensExternalDecoding)
|
|
.def("use_logits", &ModelSpec::useLogits)
|
|
.def("use_multiple_profiles", &ModelSpec::useMultipleProfiles)
|
|
.def("set_batch_sizes", &ModelSpec::setBatchSizes)
|
|
.def("set_max_input_length", &ModelSpec::setMaxInputLength)
|
|
.def("set_max_output_length", &ModelSpec::setMaxOutputLength)
|
|
.def("set_quant_method", &ModelSpec::setQuantMethod)
|
|
.def("use_lora_plugin", &ModelSpec::useLoraPlugin)
|
|
.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)
|
|
.def("get_enable_context_fmha_fp32_acc", &ModelSpec::getEnableContextFMHAFp32Acc)
|
|
.def("__copy__", [](ModelSpec const& self) { return ModelSpec(self); });
|
|
}
|
|
|
|
} // namespace tensorrt_llm::pybind::testing
|