TVM v0.7ビルド手順
CAUTION
少し古い情報(2020/9頃)のため、2021/01/16時点では不要な情報の可能性が高いが、記録のために残しておく。
ビルド
sudo apt-get update
sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev ninja-build
cd ~/workspace
git clone https://github.com/llvm/llvm-project.git
cd llvm-project && git checkout llvmorg-10.0.1 && cd ..
TVMとONNX-MLIRを共存するために、ONNX-MLIRが依存するLLVM@1d01fc(未リリースのバージョン)を使ってTVMをビルドすると、ビルドエラーが発生する。(後述)
cd ~/workspace
git clone --recursive https://github.com/apache/incubator-tvm tvm
mkdir build
cp cmake/config.cmake build
cd build
vim config.cmake
# 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 custom cmake configuration for compiling
#
# This file is used to override the build options in build.
# If you want to change the configuration, please use the following
# steps. Assume you are on the root directory. First copy the this
# file so that any local changes will be ignored by git
#
# $ mkdir build
# $ cp cmake/config.cmake build
#
# Next modify the according entries, and then compile by
#
# $ cd build
# $ cmake ..
#
# Then build in parallel with 8 threads
#
# $ make -j8
#--------------------------------------------------------------------
#---------------------------------------------
# Backend runtimes.
#---------------------------------------------
# Whether enable CUDA during compile,
#
# Possible values:
# - ON: enable CUDA with cmake's auto search
# - OFF: disable CUDA
# - /path/to/cuda: use specific path to cuda toolkit
set(USE_CUDA OFF)
# Whether enable ROCM runtime
#
# Possible values:
# - ON: enable ROCM with cmake's auto search
# - OFF: disable ROCM
# - /path/to/rocm: use specific path to rocm
set(USE_ROCM OFF)
# Whether enable SDAccel runtime
set(USE_SDACCEL OFF)
# Whether enable Intel FPGA SDK for OpenCL (AOCL) runtime
set(USE_AOCL OFF)
# Whether enable OpenCL runtime
#
# Possible values:
# - ON: enable OpenCL with cmake's auto search
# - OFF: disable OpenCL
# - /path/to/opencl-sdk: use specific path to opencl-sdk
set(USE_OPENCL OFF)
# Whether enable Metal runtime
set(USE_METAL OFF)
# Whether enable Vulkan runtime
#
# Possible values:
# - ON: enable Vulkan with cmake's auto search
# - OFF: disable vulkan
# - /path/to/vulkan-sdk: use specific path to vulkan-sdk
set(USE_VULKAN OFF)
# Whether enable OpenGL runtime
set(USE_OPENGL OFF)
# Whether enable MicroTVM runtime
set(USE_MICRO ON)
# Whether to enable SGX runtime
#
# Possible values for USE_SGX:
# - /path/to/sgxsdk: path to Intel SGX SDK
# - OFF: disable SGX
#
# SGX_MODE := HW|SIM
set(USE_SGX OFF)
set(SGX_MODE "SIM")
set(RUST_SGX_SDK "/path/to/rust-sgx-sdk")
# Whether enable RPC runtime
set(USE_RPC ON)
# Whether to build the C++ RPC server binary
set(USE_CPP_RPC ON)
# Whether embed stackvm into the runtime
set(USE_STACKVM_RUNTIME OFF)
# Whether enable tiny embedded graph runtime.
set(USE_GRAPH_RUNTIME ON)
# Whether enable additional graph debug functions
set(USE_GRAPH_RUNTIME_DEBUG ON)
# Whether enable additional vm profiler functions
set(USE_VM_PROFILER ON)
# Whether enable uTVM standalone runtime
set(USE_MICRO_STANDALONE_RUNTIME ON)
# Whether build with LLVM support
# Requires LLVM version >= 4.0
#
# Possible values:
# - ON: enable llvm with cmake's find search
# - OFF: disable llvm
# - /path/to/llvm-config: enable specific LLVM when multiple llvm-dev is available.
set(USE_LLVM /home/ubuntu/workspace/llvm-project/build/bin/llvm-config)
#---------------------------------------------
# Contrib libraries
#---------------------------------------------
# Whether use BLAS, choices: openblas, atlas, apple
set(USE_BLAS none)
# Whether to use MKL
# Possible values:
# - ON: Enable MKL
# - /path/to/mkl: mkl root path
# - OFF: Disable MKL
# set(USE_MKL /opt/intel/mkl) for UNIX
# set(USE_MKL ../IntelSWTools/compilers_and_libraries_2018/windows/mkl) for WIN32
# set(USE_MKL <path to venv or site-packages directory>) if using `pip install mkl`
set(USE_MKL OFF)
# Whether use MKLDNN library, choices: ON, OFF, path to mkldnn library
set(USE_MKLDNN OFF)
# Whether use OpenMP thread pool, choices: gnu, intel
# Note: "gnu" uses gomp library, "intel" uses iomp5 library
set(USE_OPENMP none)
# Whether use contrib.random in runtime
set(USE_RANDOM ON)
# Whether use NNPack
set(USE_NNPACK OFF)
# Possible values:
# - ON: enable tflite with cmake's find search
# - OFF: disable tflite
# - /path/to/libtensorflow-lite.a: use specific path to tensorflow lite library
set(USE_TFLITE OFF)
# /path/to/tensorflow: tensorflow root path when use tflite library
set(USE_TENSORFLOW_PATH none)
# Required for full builds with TFLite. Not needed for runtime with TFLite.
# /path/to/flatbuffers: flatbuffers root path when using tflite library
set(USE_FLATBUFFERS_PATH none)
# Possible values:
# - OFF: disable tflite support for edgetpu
# - /path/to/edgetpu: use specific path to edgetpu library
set(USE_EDGETPU OFF)
# Whether use CuDNN
set(USE_CUDNN OFF)
# Whether use cuBLAS
set(USE_CUBLAS OFF)
# Whether use MIOpen
set(USE_MIOPEN OFF)
# Whether use MPS
set(USE_MPS OFF)
# Whether use rocBlas
set(USE_ROCBLAS OFF)
# Whether use contrib sort
set(USE_SORT ON)
# Whether use MKL-DNN (DNNL) codegen
set(USE_DNNL_CODEGEN OFF)
# Whether to use Arm Compute Library (ACL) codegen
# We provide 2 separate flags since we cannot build the ACL runtime on x86.
# This is useful for cases where you want to cross-compile a relay graph
# on x86 then run on AArch.
#
# An example of how to use this can be found here: docs/deploy/arm_compute_lib.rst.
#
# USE_ARM_COMPUTE_LIB - Support for compiling a relay graph offloading supported
# operators to Arm Compute Library. OFF/ON
# USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME - Run Arm Compute Library annotated functions via the ACL
# runtime. OFF/ON/"path/to/ACL"
set(USE_ARM_COMPUTE_LIB OFF)
set(USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME OFF)
# Whether to build with Arm Ethos-N support
# Possible values:
# - OFF: disable Arm Ethos-N support
# - path/to/arm-ethos-N-stack: use a specific version of the
# Ethos-N driver stack
set(USE_ETHOSN OFF)
# If USE_ETHOSN is enabled, use ETHOSN_HW (ON) if Ethos-N hardware is available on this machine
# otherwise use ETHOSN_HW (OFF) to use the software test infrastructure
set(USE_ETHOSN_HW OFF)
# Build ANTLR parser for Relay text format
# Possible values:
# - ON: enable ANTLR by searching default locations (cmake find_program for antlr4 and /usr/local for jar)
# - OFF: disable ANTLR
# - /path/to/antlr-*-complete.jar: path to specific ANTLR jar file
set(USE_ANTLR OFF)
# Whether use Relay debug mode
set(USE_RELAY_DEBUG ON)
# Whether to build fast VTA simulator driver
set(USE_VTA_FSIM OFF)
# Whether to build cycle-accurate VTA simulator driver
set(USE_VTA_TSIM OFF)
# Whether to build VTA FPGA driver (device side only)
set(USE_VTA_FPGA OFF)
# Whether use Thrust
set(USE_THRUST OFF)
# Whether to build the TensorFlow TVMDSOOp module
set(USE_TF_TVMDSOOP OFF)
# Whether to use STL's std::unordered_map or TVM's POD compatible Map
set(USE_FALLBACK_STL_MAP OFF)
# Whether to use hexagon device
set(USE_HEXAGON_DEVICE OFF)
set(USE_HEXAGON_SDK /path/to/sdk)
# Whether to use ONNX codegen
set(USE_TARGET_ONNX ON)
# Whether to compile the standalone C runtime.
set(USE_STANDALONE_CRT ON)
cmake .. -G Ninja
ninja
export TVM_HOME=/path/to/tvm
export PYTHONPATH=$TVM_HOME/python:${PYTHONPATH}
ビルドエラーの詳細
LLVM@1d01fcを使用してTVMをビルドすると下記エラーが発生する。
[17/85] Building CXX object CMakeFiles/tvm_objs.dir/src/target/llvm/codegen_llvm.cc.o
FAILED: CMakeFiles/tvm_objs.dir/src/target/llvm/codegen_llvm.cc.o
/usr/bin/c++ -DBUILD_EXAMPLES -DDMLC_USE_FOPEN64=0 -DTVM_INDEX_DEFAULT_I64=1 -DTVM_LLVM_VERSION=120 -DTVM_THREADPOOL_USE_OPENMP=0 -DUSE_FALLBACK_STL_MAP=0 -DUSE_MICRO_STANDALONE_RUNTIME=1 -D_DEBUG -D_GNU_SOURCE -D__STDC_CONSTANT_MACROS -D__STDC_FORMAT_MACROS -D__STDC_LIMIT_MACROS -DDMLC_ENABLE_RTTI=0 -I../include -I../3rdparty/dlpack/include -I../3rdparty/dmlc-core/include -I../3rdparty/rang/include -I../3rdparty/compiler-rt -I../3rdparty/picojson -I/home/ubuntu/workspace/llvm-project/llvm/include -I/home/ubuntu/workspace/llvm-project/build/include -I../topi/include -std=c++14 -faligned-new -O2 -Wall -fPIC -fno-rtti -MD -MT CMakeFiles/tvm_objs.dir/src/target/llvm/codegen_llvm.cc.o -MF CMakeFiles/tvm_objs.dir/src/target/llvm/codegen_llvm.cc.o.d -o CMakeFiles/tvm_objs.dir/src/target/llvm/codegen_llvm.cc.o -c ../src/target/llvm/codegen_llvm.cc
../src/target/llvm/codegen_llvm.cc: In member function ‘llvm::Value* tvm::codegen::CodeGenLLVM::CreateBroadcast(llvm::Value*, int)’:
../src/target/llvm/codegen_llvm.cc:480:82: error: ‘llvm::ElementCount::ElementCount(unsigned int, bool)’ is private within this context
480 | llvm::ConstantVector::getSplat(llvm::ElementCount(lanes, /*Scalable=*/false), zero);
| ^
In file included from /home/ubuntu/workspace/llvm-project/llvm/include/llvm/IR/Type.h:24,
from /home/ubuntu/workspace/llvm-project/llvm/include/llvm/IR/DerivedTypes.h:23,
from /home/ubuntu/workspace/llvm-project/llvm/include/llvm/IR/Constants.h:31,
from /home/ubuntu/workspace/llvm-project/llvm/include/llvm/IR/Operator.h:19,
from /home/ubuntu/workspace/llvm-project/llvm/include/llvm/Analysis/TargetTransformInfo.h:24,
from ../src/target/llvm/llvm_common.h:33,
from ../src/target/llvm/codegen_llvm.h:49,
from ../src/target/llvm/codegen_llvm.cc:25:
/home/ubuntu/workspace/llvm-project/llvm/include/llvm/Support/TypeSize.h:39:3: note: declared private here
39 | ElementCount(unsigned Min, bool Scalable) : Min(Min), Scalable(Scalable) {}
| ^~~~~~~~~~~~
[22/85] Building CXX object CMakeFiles/tvm_objs.dir/src/runtime/rpc/rpc_endpoint.cc.o
ninja: build stopped: subcommand failed.
エラーメッセージを読むと、privateメソッドとして定義されているllvm::ElementCount::ElementCount(unsigned int, bool)を
クラス外から呼び出そうとしているのが原因。
実際にLLVMのTypeSize.h@1d01fcを見ると、そのように定義されている。
class ElementCount {
private:
unsigned Min; // Minimum number of vector elements.
bool Scalable; // If true, NumElements is a multiple of 'Min' determined
// at runtime rather than compile time.
/// Prevent code from using initializer-list contructors like
/// ElementCount EC = {<unsigned>, <bool>}. The static `get*`
/// methods below are preferred, as users should always make a
/// conscious choice on the type of `ElementCount` they are
/// requesting.
ElementCount(unsigned Min, bool Scalable) : Min(Min), Scalable(Scalable) {}
コメントには、下記のgetスタティックメソッドを推奨する旨が書いているが、TVM側がこの変更に追いついてないためビルドエラーが発生した。
static ElementCount get(unsigned Min, bool Scalable) {
return {Min, Scalable};
}
ElementCount(unsigned int, bool)のアクセス修飾子の変更経緯を追いかける。
b302561 (Oct 8, 2019, 9:53 PM GMT+9)で該当行を含むファイルが新規作成される。この時点でElementCount(unsigned Min, bool Scalable)はpublicメソッドとして定義されている。
class ElementCount {
public:
unsigned Min; // Minimum number of vector elements.
bool Scalable; // If true, NumElements is a multiple of 'Min' determined
// at runtime rather than compile time.
ElementCount(unsigned Min, bool Scalable)
: Min(Min), Scalable(Scalable) {}
a407ec (Aug 20, 2020, 2:26 AM GMT+9)でElementCount(unsigned Min, bool Scalable)がpublicからprivateへ変更される。(これが1d01fc時点のコード)
class ElementCount {
private:
/// Prevent code from using initializer-list contructors like
/// ElementCount EC = {<unsigned>, <bool>}. The static `get*`
/// methods below are preferred, as users should always make a
/// conscious choice on the type of `ElementCount` they are
/// requesting.
ElementCount(unsigned Min, bool Scalable) : Min(Min), Scalable(Scalable) {}
llvmorg-10.0.1はb302561のコードを使用している(=publicメソッドとして定義されている)ため、問題なくビルドできる。