/* * SPDX-FileCopyrightText: Copyright (c) 1993-2023 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 "gemmSwigluPlugin.h" #include "cutlass/util/reference/device/tensor_fill.h" #include "cutlass_extensions/gemm_configs.h" using namespace nvinfer1; using namespace tensorrt_llm::common; using namespace tensorrt_llm::kernels::cutlass_kernels; using tensorrt_llm::plugins::GemmSwigluPluginCreator; using tensorrt_llm::plugins::GemmSwigluPlugin; using tensorrt_llm::plugins::GemmSwigluPluginProfiler; using tensorrt_llm::plugins::read; using tensorrt_llm::plugins::write; void GemmSwigluPluginProfiler::initTmpData(int m, int n, int k, char* workspace, size_t size, cudaStream_t stream) { size_t bpe = getBytePerElement(mType); if (mType == nvinfer1::DataType::kFP8) { cutlass::reference::device::BlockFillRandomUniform(reinterpret_cast(workspace), m * k + n * k + 1 * n, 42, cutlass::float_e4m3_t{128}, -cutlass::float_e4m3_t{128}, -1, 0, stream); } }