# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. #------------------------------------------------------------------------------- # Template configuration for compiling MXNet # # If you want to change the configuration, please use the following steps. # Assume you are on the root directory of mxnet. First copy this file so that # any local changes will be ignored by git # # $ cp config/darwin.cmake config.cmake # # Next modify the according entries, and then compile by # # $ mkdir build; cd build # $ cmake .. # $ cmake --build . # # Specify `cmake --build . --parallel N` to set the number of parallel compilation jobs. # Default is derived from CPUs available. # #------------------------------------------------------------------------------- #--------------------------------------------- # Common libraries #--------------------------------------------- set(USE_BLAS "apple" CACHE STRING "BLAS Vendor") set(OpenCV_DIR /opt/local/libexec/opencv3/cmake) set(USE_OPENCV ON CACHE BOOL "Build with OpenCV support") set(OPENCV_ROOT "" CACHE BOOL "OpenCV install path. Supports autodetection.") set(USE_OPENMP OFF CACHE BOOL "Build with Openmp support") set(USE_ONEDNN ON CACHE BOOL "Build with oneDNN support") set(USE_LAPACK ON CACHE BOOL "Build with lapack support") set(USE_TVM_OP OFF CACHE BOOL "Enable use of TVM operator build system.") #--------------------- # Compilers #-------------------- # Compilers are usually autodetected. Uncomment and modify the next 3 lines to # choose manually: # set(CMAKE_C_COMPILER "" CACHE BOOL "C compiler") # set(CMAKE_CXX_COMPILER "" CACHE BOOL "C++ compiler") # set(CMAKE_CUDA_COMPILER "" CACHE BOOL "Cuda compiler (nvcc)") #--------------------------------------------- # CPU instruction sets: The support is autodetected if turned ON #--------------------------------------------- set(USE_SSE ON CACHE BOOL "Build with x86 SSE instruction support") set(USE_F16C ON CACHE BOOL "Build with x86 F16C instruction support") #---------------------------- # distributed computing #---------------------------- set(USE_DIST_KVSTORE OFF CACHE BOOL "Build with DIST_KVSTORE support") #---------------------------- # performance settings #---------------------------- set(USE_OPERATOR_TUNING ON CACHE BOOL "Enable auto-tuning of operators") set(USE_GPERFTOOLS OFF CACHE BOOL "Build with GPerfTools support") set(USE_JEMALLOC OFF CACHE BOOL "Build with Jemalloc support") #---------------------------- # additional operators #---------------------------- # path to folders containing projects specific operators that you don't want to # put in src/operators SET(EXTRA_OPERATORS "" CACHE PATH "EXTRA OPERATORS PATH") #--------------------------------------------- # GPU support #--------------------------------------------- set(USE_CUDA OFF CACHE BOOL "Build with CUDA support") set(USE_CUDNN OFF CACHE BOOL "Build with cudnn support, if found") set(USE_CUTENSOR OFF CACHE BOOL "Build with cutensor support, if found") # Target NVIDIA GPU achitecture. # Valid options are "Auto" for autodetection, "All" for all available # architectures or a list of architectures by compute capability number, such as # "7.0" or "7.0;7.5" as well as name, such as "Volta" or "Volta;Turing". # The value specified here is passed to cmake's CUDA_SELECT_NVCC_ARCH_FLAGS to # obtain the compilation flags for nvcc. # # When compiling on a machine without GPU, autodetection will fail and you # should instead specify the target architecture manually to avoid excessive # compilation times. set(MXNET_CUDA_ARCH "Auto" CACHE STRING "Target NVIDIA GPU achitecture") #---------------------------- # other features #---------------------------- # Create C++ interface package set(USE_CPP_PACKAGE OFF CACHE BOOL "Build C++ Package") # Use int64_t type to represent the total number of elements in a tensor # This will cause performance degradation reported in issue #14496 # Set to 1 for large tensor with tensor size greater than INT32_MAX i.e. 2147483647 # Note: the size of each dimension is still bounded by INT32_MAX set(USE_INT64_TENSOR_SIZE ON CACHE BOOL "Use int64_t to represent the total number of elements in a tensor") # Other GPU features set(USE_NCCL "Use NVidia NCCL with CUDA" OFF) set(NCCL_ROOT "" CACHE BOOL "NCCL install path. Supports autodetection.") set(USE_NVTX ON CACHE BOOL "Build with NVTX support")