# 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(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 OFF 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")