Merge pull request #226 from lzhengning/macOS

Mac os support
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Zheng-Ning Liu 2021-06-21 21:05:11 +08:00 committed by GitHub
commit ae2eafd878
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50 changed files with 453 additions and 154 deletions

1
.gitignore vendored
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@ -1,5 +1,6 @@
my
.refresh
.DS_Store
__pycache__
.ipynb_checkpoints/
.vscode/

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@ -89,7 +89,7 @@ for i,(x,y) in enumerate(get_data(n)):
Jittor框架对环境要求如下:
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch) 或 **Windows Subsystem of LinuxWSL**
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**x86_64或 **Windows Subsystem of LinuxWSL**
* Python版本 >= 3.7
* C++编译器 (需要下列至少一个)
- g++ >=5.4.0
@ -100,7 +100,9 @@ Jittor框架对环境要求如下:
如果您不希望手动配置环境,我们推荐使用 Docker 进行安装。
除此之外,您还可以使用 pip 安装和手动安装。
注意目前Jittor通过WSL的方式在Windows操作系统上运行WSL的安装方法请参考[微软官网](https://docs.microsoft.com/en-us/windows/wsl/install-win10)WSL版本目前尚不支持CUDA。
注意1目前Jittor通过WSL的方式在Windows操作系统上运行WSL的安装方法请参考[微软官网](https://docs.microsoft.com/en-us/windows/wsl/install-win10)WSL版本目前尚不支持CUDA。
注意2macOS 用户需要安装额外依赖,请参考 [macOS 安装](#macOS-安装)。
Jittor 提供了三种安装方法dockerpip和手动安装
@ -112,6 +114,7 @@ Jittor 提供了三种安装方法dockerpip和手动安装
## Docker 安装
我们提供了Docker安装方式免去您配置环境Docker安装方法如下
@ -145,6 +148,27 @@ python3.7 -m jittor.test.test_example
如果测试运行通过,恭喜你已经安装完成.
jittor会自动在路径中寻找合适的编译器, 如果您希望手动指定编译器, 请使用环境变量 `cc_path``nvcc_path`(可选).
## macOS 安装
macOS 请使用 [homebrew](https://brew.sh) 安装额外的依赖 (python>=3.7, onednn)。
```bash
brew install python@3.7 onednn libomp
```
之后您可以通过 pip 安装 jittor并测试是否可以成功运行。
```bash
python3.7 -m pip install jittor
python3.7 -m jittor.test.test_example
```
目前在macOS中jittor 只支持 CPU 计算。
## 手动安装

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@ -92,9 +92,10 @@ We provide some jupyter notebooks to help you quick start with Jittor.
Jittor environment requirements:
* System: **Linux**(e.g. Ubuntu/CentOS/Arch) (or **Windows** Subsystem of Linux)
* System: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**, or **Windows Subsystem of Linux (WSL)**
* Python version >= 3.7
* CPU compiler (require at least one of the following)
* g++ (>=5.4.0)
@ -105,7 +106,9 @@ Jittor environment requirements:
Note: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
Note#1: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
Note#2: macOS users have to install additional dependencies, see [macOS install](#macOS-install).
Jittor offers three ways to install: docker, pip, or manual.
@ -139,6 +142,27 @@ python3.7 -m jittor.test.test_example
```
## macOS install
Please first install additional dependencies with [homebrew](https://brew.sh).
```bash
brew install python@3.7 onednn libomp
```
Then you can install jittor through pip and run the example.
```bash
python3.7 -m pip install jittor
python3.7 -m jittor.test.test_example
```
Currently jittor only supports CPU in macOS.
## manual install
We will show how to install Jittor in Ubuntu 16.04 step by step, Other Linux distributions may have similar commands.

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@ -113,7 +113,7 @@ We provide some jupyter notebooks to help you quick start with Jittor.
Jittor框架对环境要求如下:
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch) 或 **Windows Subsystem of LinuxWSL**
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**x86_64或 **Windows Subsystem of LinuxWSL**
* Python版本 >= 3.7
* C++编译器 (需要下列至少一个)
- g++ >=5.4.0
@ -124,13 +124,15 @@ Jittor框架对环境要求如下:
如果您不希望手动配置环境,我们推荐使用 Docker 进行安装。
除此之外,您还可以使用 pip 安装和手动安装。
注意目前Jittor通过WSL的方式在Windows操作系统上运行WSL的安装方法请参考[微软官网](https://docs.microsoft.com/en-us/windows/wsl/install-win10)WSL版本目前尚不支持CUDA。
注意1目前Jittor通过WSL的方式在Windows操作系统上运行WSL的安装方法请参考[微软官网](https://docs.microsoft.com/en-us/windows/wsl/install-win10)WSL版本目前尚不支持CUDA。
注意2macOS 用户需要安装额外依赖,请参考 [macOS 安装](#macOS-安装)。
Jittor 提供了三种安装方法dockerpip和手动安装
Jittor environment requirements:
* System: **Linux**(e.g. Ubuntu/CentOS/Arch) (or **Windows** Subsystem of Linux)
* System: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**, or **Windows Subsystem of Linux (WSL)**
* Python version >= 3.7
* CPU compiler (require at least one of the following)
* g++ (>=5.4.0)
@ -141,7 +143,9 @@ Jittor environment requirements:
Note: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
Note#1: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
Note#2: macOS users have to install additional dependencies, see [macOS install](#macOS-install).
Jittor offers three ways to install: docker, pip, or manual.
@ -183,6 +187,31 @@ python3.7 -m jittor.test.test_example
如果测试运行通过,恭喜你已经安装完成.
jittor会自动在路径中寻找合适的编译器, 如果您希望手动指定编译器, 请使用环境变量 `cc_path``nvcc_path`(可选).
## macOS 安装
## macOS install
macOS 请使用 [homebrew](https://brew.sh) 安装额外的依赖 (python>=3.7, onednn)。
Please first install additional dependencies with [homebrew](https://brew.sh).
```bash
brew install python@3.7 onednn libomp
```
之后您可以通过 pip 安装 jittor并测试是否可以成功运行。
Then you can install jittor through pip and run the example.
```bash
python3.7 -m pip install jittor
python3.7 -m jittor.test.test_example
```
目前在macOS中jittor 只支持 CPU 计算。
Currently jittor only supports CPU in macOS.
## 手动安装
## manual install

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@ -1169,9 +1169,11 @@ def dirty_fix_pytorch_runtime_error():
jt.dirty_fix_pytorch_runtime_error()
import torch
'''
import os
os.RTLD_GLOBAL = os.RTLD_GLOBAL | os.RTLD_DEEPBIND
import os, platform
if platform.system() == 'Linux':
os.RTLD_GLOBAL = os.RTLD_GLOBAL | os.RTLD_DEEPBIND
import atexit

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@ -5,6 +5,7 @@
# file 'LICENSE.txt', which is part of this source code package.
# ***************************************************************
import os, sys, shutil
import platform
from .compiler import *
from jittor_utils import run_cmd, get_version, get_int_version
from jittor_utils.misc import download_url_to_local
@ -74,39 +75,49 @@ def setup_mkl():
mkl_include_path = os.environ.get("mkl_include_path")
mkl_lib_path = os.environ.get("mkl_lib_path")
if mkl_lib_path is None or mkl_include_path is None:
mkl_install_sh = os.path.join(jittor_path, "script", "install_mkl.sh")
LOG.v("setup mkl...")
# mkl_path = os.path.join(cache_path, "mkl")
# mkl_path decouple with cc_path
from pathlib import Path
mkl_path = os.path.join(str(Path.home()), ".cache", "jittor", "mkl")
make_cache_dir(mkl_path)
install_mkl(mkl_path)
mkl_home = ""
for name in os.listdir(mkl_path):
if name.startswith("dnnl") and os.path.isdir(os.path.join(mkl_path, name)):
mkl_home = os.path.join(mkl_path, name)
break
assert mkl_home!=""
if platform.system() == 'Linux':
if mkl_lib_path is None or mkl_include_path is None:
mkl_install_sh = os.path.join(jittor_path, "script", "install_mkl.sh")
LOG.v("setup mkl...")
# mkl_path = os.path.join(cache_path, "mkl")
# mkl_path decouple with cc_path
from pathlib import Path
mkl_path = os.path.join(str(Path.home()), ".cache", "jittor", "mkl")
make_cache_dir(mkl_path)
install_mkl(mkl_path)
mkl_home = ""
for name in os.listdir(mkl_path):
if name.startswith("dnnl") and os.path.isdir(os.path.join(mkl_path, name)):
mkl_home = os.path.join(mkl_path, name)
break
assert mkl_home!=""
mkl_include_path = os.path.join(mkl_home, "include")
mkl_lib_path = os.path.join(mkl_home, "lib")
mkl_lib_name = os.path.join(mkl_lib_path, "libmkldnn.so")
assert os.path.isdir(mkl_include_path)
assert os.path.isdir(mkl_lib_path)
assert os.path.isfile(mkl_lib_name)
LOG.v(f"mkl_include_path: {mkl_include_path}")
LOG.v(f"mkl_lib_path: {mkl_lib_path}")
LOG.v(f"mkl_lib_name: {mkl_lib_name}")
# We do not link manualy, link in custom ops
# ctypes.CDLL(mkl_lib_name, dlopen_flags)
mkl_lib_name = os.path.join(mkl_lib_path, "libmkldnn.so")
assert os.path.isdir(mkl_include_path)
assert os.path.isdir(mkl_lib_path)
assert os.path.isfile(mkl_lib_name)
LOG.v(f"mkl_include_path: {mkl_include_path}")
LOG.v(f"mkl_lib_path: {mkl_lib_path}")
LOG.v(f"mkl_lib_name: {mkl_lib_name}")
# We do not link manualy, link in custom ops
# ctypes.CDLL(mkl_lib_name, dlopen_flags)
extra_flags = f" -I'{mkl_include_path}' -L'{mkl_lib_path}' -lmkldnn -Wl,-rpath='{mkl_lib_path}' "
elif platform.system() == 'Darwin':
mkl_lib_paths = [
"/usr/local/lib/libmkldnn.dylib", # x86_64
"/opt/homebrew/lib/libmkldnn.dylib", # arm64
]
if not any([os.path.exists(lib) for lib in mkl_lib_paths]):
raise RuntimeError("Not found onednn, please install it by the command 'brew install onednn@2.2.3'")
extra_flags = f" -lmkldnn "
mkl_op_dir = os.path.join(jittor_path, "extern", "mkl", "ops")
mkl_op_files = [os.path.join(mkl_op_dir, name) for name in os.listdir(mkl_op_dir)]
mkl_ops = compile_custom_ops(mkl_op_files,
extra_flags=f" -I'{mkl_include_path}' -L'{mkl_lib_path}' -lmkldnn -Wl,-rpath='{mkl_lib_path}' ")
mkl_ops = compile_custom_ops(mkl_op_files, extra_flags=extra_flags)
LOG.vv("Get mkl_ops: "+str(dir(mkl_ops)))

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@ -11,6 +11,7 @@ import sys
import inspect
import datetime
import threading
import platform
import ctypes
import platform
from ctypes import cdll
@ -94,7 +95,7 @@ def compile(compiler, flags, inputs, output, combind_build=False):
return do_compile(cmd)
def gen_jit_tests():
all_src = run_cmd('find -L src/ | grep "cc$"', jittor_path).splitlines()
all_src = run_cmd('find -L src | grep "cc$"', jittor_path).splitlines()
jit_declares = []
re_def = re.compile("JIT_TEST\\((.*?)\\)")
names = set()
@ -144,7 +145,7 @@ def gen_jit_tests():
f.write(jit_src)
def gen_jit_flags():
all_src = run_cmd('find -L src/ | grep "cc$"', jittor_path).splitlines()
all_src = run_cmd('find -L src | grep "cc$"', jittor_path).splitlines()
jit_declares = []
re_def = re.compile("DEFINE_FLAG(_WITH_SETTER)?\\((.*?)\\);", re.DOTALL)
@ -593,7 +594,7 @@ def compile_custom_ops(
filenames,
extra_flags="",
return_module=False,
dlopen_flags=os.RTLD_GLOBAL | os.RTLD_NOW | os.RTLD_DEEPBIND,
dlopen_flags=None,
gen_name_ = ""):
"""Compile custom ops
filenames: path of op source files, filenames must be
@ -603,6 +604,11 @@ def compile_custom_ops(
return_module: return module rather than ops(default: False)
return: compiled ops
"""
if dlopen_flags is None:
dlopen_flags = os.RTLD_GLOBAL | os.RTLD_NOW
if platform.system() == 'Linux':
dlopen_flags |= os.RTLD_DEEPBIND
srcs = {}
headers = {}
builds = []
@ -701,7 +707,7 @@ def get_full_path_of_executable(name):
def compile_extern():
# compile llvm passes
if cc_type != "clang":
if cc_type != "clang" or platform.system() != 'Linux':
return
global kernel_opt_flags
cache_path_llvm = os.path.join(cache_path, "llvm")
@ -842,11 +848,15 @@ def check_debug_flags():
cc_flags = " "
# os.RTLD_NOW | os.RTLD_GLOBAL cause segfault when import torch first
import_flags = os.RTLD_NOW | os.RTLD_GLOBAL | os.RTLD_DEEPBIND
import_flags = os.RTLD_NOW | os.RTLD_GLOBAL
if platform.system() == 'Linux':
import_flags |= os.RTLD_DEEPBIND
# if cc_type=="icc":
# # weird link problem, icc omp library may conflict and cause segfault
# import_flags = os.RTLD_NOW | os.RTLD_GLOBAL
dlopen_flags = os.RTLD_NOW | os.RTLD_GLOBAL | os.RTLD_DEEPBIND
dlopen_flags = os.RTLD_NOW | os.RTLD_GLOBAL
if platform.system() == 'Linux':
import_flags |= os.RTLD_DEEPBIND
with jit_utils.import_scope(import_flags):
jit_utils.try_import_jit_utils_core()
@ -894,14 +904,35 @@ gdb_path = try_find_exe('gdb')
addr2line_path = try_find_exe('addr2line')
has_pybt = check_pybt(gdb_path, python_path)
cc_flags += " -Wall -Werror -Wno-unknown-pragmas -std=c++14 -fPIC -march=native "
cc_flags += " -Wall -Werror -Wno-unknown-pragmas -std=c++14 -fPIC "
# 1. Arch/CPU specific optimization
if platform.machine() == "x86_64":
cc_flags += " -march=native "
elif platform.machine() == 'arm64' and platform.system() == "Darwin":
cc_flags += " -mcpu=apple-a14 "
cc_flags += " -fdiagnostics-color=always "
# 2. Non standard include path
if platform.system() == 'Darwin' and platform.machine() == 'arm64':
cc_flags += " -I/opt/homebrew/include "
# 3. User specified flags
if "cc_flags" in os.environ:
cc_flags += os.environ["cc_flags"] + ' '
link_flags = " -lstdc++ -ldl -shared "
if platform.system() == 'Darwin':
# TODO: if not using apple clang, there is no need to add -lomp
link_flags += "-undefined dynamic_lookup -lomp "
if platform.machine() == "arm64":
link_flags += " -L/opt/homebrew/lib "
core_link_flags = ""
opt_flags = ""
kernel_opt_flags = os.environ.get("kernel_flags", "") + opt_flags + " -fopenmp "
kernel_opt_flags = os.environ.get("kernel_flags", "") + opt_flags
if platform.system() == 'Darwin':
# TODO: if not using apple clang, cannot add -Xpreprocessor
kernel_opt_flags = kernel_opt_flags + " -Xpreprocessor -fopenmp "
else:
kernel_opt_flags = kernel_opt_flags + " -fopenmp "
if ' -O' not in cc_flags:
opt_flags += " -O2 "
@ -960,7 +991,7 @@ if has_cuda:
# build core
gen_jit_flags()
gen_jit_tests()
op_headers = run_cmd('find -L src/ops/ | grep "op.h$"', jittor_path).splitlines()
op_headers = run_cmd('find -L src/ops | grep "op.h$"', jittor_path).splitlines()
jit_src = gen_jit_op_maker(op_headers)
LOG.vvvv(jit_src)
with open(os.path.join(cache_path, "gen", "jit_op_maker.h"), 'w') as f:
@ -1008,19 +1039,26 @@ LOG.vv("compile order:", files)
# manual Link omp using flags(os.RTLD_NOW | os.RTLD_GLOBAL)
# if cc_type=="icc":
# os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
libname = {"clang":"omp", "icc":"iomp5", "g++":"gomp"}[cc_type]
libname = ctypes.util.find_library(libname)
assert libname is not None, "openmp library not found"
ctypes.CDLL(libname, os.RTLD_NOW | os.RTLD_GLOBAL)
if platform.system() == 'Linux':
libname = {"clang":"omp", "icc":"iomp5", "g++":"gomp"}[cc_type]
libname = ctypes.util.find_library(libname)
assert libname is not None, "openmp library not found"
ctypes.CDLL(libname, os.RTLD_NOW | os.RTLD_GLOBAL)
# get os release
with open("/etc/os-release", "r", encoding='utf8') as f:
s = f.read().splitlines()
os_release = {}
for line in s:
a = line.split('=')
if len(a) != 2: continue
os_release[a[0]] = a[1].replace("\"", "")
if platform.system() == 'Linux':
with open("/etc/os-release", "r", encoding='utf8') as f:
s = f.read().splitlines()
os_release = {}
for line in s:
a = line.split('=')
if len(a) != 2: continue
os_release[a[0]] = a[1].replace("\"", "")
os_arch = ''
elif platform.system() == 'Darwin':
os_release = {'ID' : 'macos'}
os_arch = platform.machine()
os_type = {
"ubuntu": "ubuntu",
@ -1028,7 +1066,9 @@ os_type = {
"centos": "centos",
"rhel": "ubuntu",
"fedora": "ubuntu",
"macos": "macos",
}
version_file = os.path.join(jittor_path, "version")
if os.path.isfile(version_file) and not os.path.isdir(os.path.join(jittor_path, "src", "__data__")):
with open(version_file, 'r') as f:
@ -1036,7 +1076,8 @@ if os.path.isfile(version_file) and not os.path.isdir(os.path.join(jittor_path,
# key = f"{version}-{cc_type}-{'cuda' if has_cuda else 'cpu'}.o"
key = f"{version}-g++-cpu"
os_id = os_release["ID"]
os_key = os_type.get(os_id, "ubuntu")
os_key = os_type.get(os_id, "ubuntu")
os_key += '-' + os_arch if os_arch else ''
if "os_key" in os.environ:
os_key = os.environ['os_key']
if platform.machine()=='aarch64':

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@ -860,8 +860,8 @@ def compile_single(head_file_name, src_file_name, src=None):
return True
def compile(cache_path, jittor_path):
headers1 = run_cmd('find -L src/ | grep ".h$"', jittor_path).splitlines()
headers2 = run_cmd('find gen/ | grep ".h$"', cache_path).splitlines()
headers1 = run_cmd('find -L src | grep ".h$"', jittor_path).splitlines()
headers2 = run_cmd('find gen | grep ".h$"', cache_path).splitlines()
headers = [ os.path.join(jittor_path, h) for h in headers1 ] + \
[ os.path.join(cache_path, h) for h in headers2 ]
basenames = []

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@ -33,7 +33,11 @@ jit_op_entry_t load_jit_lib(string name, string symbol_name="jit_entry") {
LOGvv << "Opening jit lib:" << name;
// void* handle = dlopen(name.c_str(), RTLD_NOW | RTLD_DEEPBIND | RTLD_LOCAL);
// RTLD_DEEPBIND and openmp cause segfault
#ifdef __linux__
void* handle = dlopen(name.c_str(), RTLD_NOW | RTLD_LOCAL | RTLD_DEEPBIND);
#else
void *handle = dlopen(name.c_str(), RTLD_NOW | RTLD_LOCAL);
#endif
CHECK(handle) << "Cannot open library" << name << ":" << dlerror();
//dlerror();
@ -84,8 +88,11 @@ jit_op_entry_t compile(const string& jit_key, const string& src, const bool is_c
+ " '" + jit_src_path + "'" + other_src
+ cc_flags + extra_flags
+ " -o '" + jit_lib_path + "'";
#ifdef __linux__
cmd = python_path+" "+jittor_path+"/utils/asm_tuner.py "
"--cc_path=" + cmd;
#endif
}
cache_compile(cmd, cache_path, jittor_path);
auto symbol_name = get_symbol_name(jit_key);

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@ -6,13 +6,12 @@
// ***************************************************************
#include <sys/mman.h>
#include <sstream>
#include <unistd.h>
#include "jit_key.h"
#include "utils/str_utils.h"
namespace jittor {
const int page_size = 4*1024;
extern thread_local size_t protected_page;
static size_t get_buffer_end_page(size_t buffer_end) {
@ -21,23 +20,23 @@ static size_t get_buffer_end_page(size_t buffer_end) {
// | | | | |
// buffer: xxxxxxxxxxxxxxxxxxxxxxxx
// ^ buffer_end_page
size_t buffer_end_page = buffer_end - buffer_end % page_size;
if (buffer_end_page + page_size-1 > buffer_end)
buffer_end_page -= page_size;
size_t buffer_end_page = buffer_end - buffer_end % getpagesize();
if (buffer_end_page + getpagesize()-1 > buffer_end)
buffer_end_page -= getpagesize();
return buffer_end_page;
}
JitKey::JitKey() {
auto buffer_end_page = get_buffer_end_page((size_t)&buffer[buffer_size-1]);
LOGvv << "protect page" << (void*)buffer_end_page;
ASSERT(0==mprotect((void*)buffer_end_page, page_size, PROT_NONE));
ASSERT(0==mprotect((void*)buffer_end_page, getpagesize(), PROT_NONE));
protected_page = buffer_end_page;
}
JitKey::~JitKey() {
auto buffer_end_page = get_buffer_end_page((size_t)&buffer[buffer_size-1]);
LOGvv << "un-protect page" << (void*)buffer_end_page;
mprotect((void*)buffer_end_page, page_size, PROT_READ|PROT_WRITE|PROT_EXEC);
mprotect((void*)buffer_end_page, getpagesize(), PROT_READ|PROT_WRITE|PROT_EXEC);
protected_page = 0;
}

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@ -166,9 +166,11 @@ inline JK& operator<<(JK& jk, int64 c) {
return jk << JK::hex(c);
}
#ifdef __linux__
inline JK& operator<<(JK& jk, long long int c) {
return jk << (int64)c;
}
#endif
inline JK& operator<<(JK& jk, uint64 c) {
return jk << JK::hex(c);

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@ -14,6 +14,9 @@ AlignedAllocator aligned_allocator;
const char* AlignedAllocator::name() const {return "aligned";}
void* AlignedAllocator::alloc(size_t size, size_t& allocation) {
#ifdef __APPLE__
size += 32-size%32;
#endif
return aligned_alloc(alignment, size);
}

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@ -6,7 +6,12 @@
// ***************************************************************
#include <iomanip>
#include <algorithm>
#if defined(__linux__)
#include <sys/sysinfo.h>
#elif defined(__APPLE__)
#include <sys/sysctl.h>
#endif
#include "var.h"
#include "op.h"
@ -152,9 +157,17 @@ void display_memory_info(const char* fileline, bool dump_var, bool red_color) {
}
MemInfo::MemInfo() {
#if defined(__linux__)
struct sysinfo info = {0};
sysinfo(&info);
total_cpu_ram = info.totalram;
#elif defined(__APPLE__)
int mib[] = {CTL_HW, HW_MEMSIZE};
int64 mem;
size_t len;
total_cpu_ram = sysctl(mib, 2, &mem, &len, NULL, 0);
#endif
total_cuda_ram = 0;
#ifdef HAS_CUDA
cudaDeviceProp prop;

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@ -14,7 +14,6 @@
#include "mem/allocator/sfrl_allocator.h"
#include <iomanip>
#include <algorithm>
#include <sys/sysinfo.h>
#include <sstream>
#include "pybind/py_var_tracer.h"

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@ -4,7 +4,7 @@
// This file is subject to the terms and conditions defined in
// file 'LICENSE.txt', which is part of this source code package.
// ***************************************************************
#include <bits/stdc++.h>
#include <cstring>
#include "misc/nano_string.h"
namespace jittor {

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@ -159,13 +159,8 @@ struct NanoVector {
for (auto a : v) push_back_check_overflow(a);
}
inline static NanoVector make(const int64* v, int n) {
NanoVector nv;
for (int i=0; i<n; i++) nv.push_back_check_overflow(v[i]);
return nv;
}
inline static NanoVector make(const int32* v, int n) {
template<typename TMakeV>
inline static NanoVector make(const TMakeV* v, int n) {
NanoVector nv;
for (int i=0; i<n; i++) nv.push_back_check_overflow(v[i]);
return nv;

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@ -51,7 +51,9 @@ struct RingBuffer {
// a dirty hack
// ref: https://stackoverflow.com/questions/20439404/pthread-conditions-and-process-termination
// cv.__data.__wrefs = 0;
#ifdef __linux__
cv.__data = {0};
#endif
pthread_cond_destroy(&cv);
}

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@ -5,12 +5,22 @@
// file 'LICENSE.txt', which is part of this source code package.
// ***************************************************************
#pragma once
#if defined(__clang__)
#include <string_view>
#elif defined(__GNUC__)
#include <experimental/string_view>
#endif
#include "common.h"
namespace jittor {
#if defined(__clang__)
using std::string_view;
#elif defined(__GNUC__)
using std::experimental::string_view;
#endif
template<class T>
struct string_view_map {

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@ -144,7 +144,8 @@ void GetitemOp::infer_slices(
out_shape_j = (slice.stop - slice.start - 1) / slice.step + 1;
else
out_shape_j = (slice.start - slice.stop - 1) / -slice.step + 1;
out_shape_j = std::max(0l, out_shape_j);
out_shape_j = out_shape_j > 0 ? out_shape_j : 0;
}
out_shape.push_back(out_shape_j);
}

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@ -103,7 +103,9 @@ void LoopToFuncPass::run() {
auto& fc = ir->children[i];
fc->attrs["loop_func"] = func->attrs["lvalue"];
}
// ir->remove_all_unused();
#ifdef __APPLE__
ir->remove_all_unused();
#endif
}
} // jittor

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@ -58,7 +58,11 @@ void Profiler::stop() {
unique_ptr<MemoryChecker>* load_memory_checker(string name) {
LOGvv << "Opening jit lib:" << name;
void* handle = dlopen(name.c_str(), RTLD_LAZY | RTLD_DEEPBIND | RTLD_LOCAL);
#ifdef __linux__
void *handle = dlopen(name.c_str(), RTLD_LAZY | RTLD_DEEPBIND | RTLD_LOCAL);
#else
void* handle = dlopen(name.c_str(), RTLD_LAZY | RTLD_LOCAL);
#endif
CHECK(handle) << "Cannot open library" << name << ":" << dlerror();
//dlerror();

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@ -140,7 +140,11 @@ ArrayOp::ArrayOp(PyObject* obj) {
std::memcpy(host_ptr, args.ptr, size);
} else {
// this is non-continue numpy array
#if defined(__linux__)
int64 dims[args.shape.size()];
#elif defined(__APPLE__)
long dims[args.shape.size()];
#endif
for (int i=0; i<args.shape.size(); i++)
dims[i] = args.shape[i];
holder.assign(PyArray_New(

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@ -266,7 +266,11 @@ DEF_IS(ArrayArgs, bool) is_type(PyObject* obj) {
}
DEF_IS(ArrayArgs, PyObject*) to_py_object(const T& a) {
#if defined(__linux__)
int64 dims[a.shape.size()];
#elif defined(__APPLE__)
long dims[a.shape.size()];
#endif
for (int i=0; i<a.shape.size(); i++)
dims[i] = a.shape[i];
PyObjHolder obj(PyArray_SimpleNew(
@ -378,7 +382,11 @@ DEF_IS(VarHolder*, T) from_py_object(PyObject* obj, unique_ptr<VarHolder>& holde
struct DataView;
DEF_IS(DataView, PyObject*) to_py_object(T a) {
#if defined(__linux__)
int64 dims[a.shape.size()];
#elif defined(__APPLE__)
long dims[a.shape.size()];
#endif
for (int i=0; i<a.shape.size(); i++)
dims[i] = a.shape[i];
PyObjHolder oh(PyArray_New(

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@ -109,7 +109,11 @@ static void push_py_object(RingBuffer* rb, PyObject* obj, uint64& __restrict__ o
rb->push_t<NanoString>(args.dtype, offset);
rb->push(size, offset);
args.ptr = rb->get_ptr(size, offset);
#if defined(__linux__)
int64 dims[args.shape.size()];
#elif defined(__APPLE__)
long dims[args.shape.size()];
#endif
for (int i=0; i<args.shape.size(); i++)
dims[i] = args.shape[i];
PyObjHolder oh(PyArray_New(

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@ -411,8 +411,19 @@ inline Console() {
#endif
run("import jittor as jt");
make_pyjt_array = (PyObject* (*)(const vector<int64>& shape, const string& dtype, const void* data))dlsym(RTLD_DEFAULT, "_ZN6jittor15make_pyjt_arrayERKSt6vectorIlSaIlEERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPKv");
get_pyjt_array = (void (*)(PyObject* obj, vector<int64>& shape, string& dtype, void*& data))dlsym(RTLD_DEFAULT, "_ZN6jittor14get_pyjt_arrayEP7_objectRSt6vectorIlSaIlEERNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERPv");
#ifdef __APPLE__
auto symbol_make_pyjt_array = "__ZN6jittor15make_pyjt_arrayERKNSt3__16vectorIxNS0_9allocatorIxEEEERKNS0_12basic_stringIcNS0_11char_traitsIcEENS2_IcEEEEPKv";
auto symbol_gen_pyjt_array = "__ZN6jittor14get_pyjt_arrayEP7_objectRNSt3__16vectorIxNS2_9allocatorIxEEEERNS2_12basic_stringIcNS2_11char_traitsIcEENS4_IcEEEERPv";
#else
auto symbol_make_pyjt_array = "_ZN6jittor15make_pyjt_arrayERKSt6vectorIlSaIlEERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPKv";
auto symbol_gen_pyjt_array = "_ZN6jittor14get_pyjt_arrayEP7_objectRSt6vectorIlSaIlEERNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERPv";
#endif
make_pyjt_array = (PyObject* (*)(const vector<int64>& shape, const string& dtype, const void* data))dlsym(RTLD_DEFAULT, symbol_make_pyjt_array);
get_pyjt_array = (void (*)(PyObject* obj, vector<int64>& shape, string& dtype, void*& data))dlsym(RTLD_DEFAULT, symbol_gen_pyjt_array);
if (!make_pyjt_array || !get_pyjt_array) {
std::cerr << "get symbol failed." << std::endl;
exit(1);
}
}
inline ~Console() {

View File

@ -196,6 +196,8 @@ bool cache_compile(const string& cmd, const string& cache_path, const string& ji
for (size_t i=0; i<input_names.size(); i++) {
if (processed.count(input_names[i]) != 0)
continue;
if (input_names[i] == "dynamic_lookup")
continue;
processed.insert(input_names[i]);
auto src = read_all(input_names[i]);
ASSERT(src.size()) << "Source read failed:" << input_names[i];

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@ -12,7 +12,11 @@
#endif
#ifdef __GNUC__
#endif
#ifdef __linux__
#include <sys/prctl.h>
#endif
#include <signal.h>
#include <iterator>
#include <algorithm>
@ -21,7 +25,10 @@
namespace jittor {
void init_subprocess() {
#ifdef __linux__
prctl(PR_SET_PDEATHSIG, SIGKILL);
#endif
}
static void __log(

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@ -194,7 +194,11 @@ void segfault_sigaction(int signal, siginfo_t *si, void *arg) {
LOGe << "Caught SIGINT, quick exit";
}
exited = true;
#ifdef __APPLE__
_Exit(1);
#else
std::quick_exit(1);
#endif
}
std::cerr << "Caught segfault at address " << si->si_addr << ", "
<< "thread_name: '" << thread_name << "', flush log..." << std::endl;

View File

@ -7,8 +7,10 @@
#include <stdio.h>
#include <stdlib.h>
#include <sys/wait.h>
#include <unistd.h>
#ifdef __linux__
#include <sys/prctl.h>
#endif
#include <unistd.h>
#include <execinfo.h>
#include <iostream>
#include "utils/tracer.h"
@ -61,7 +63,9 @@ void setter_gdb_attach(int v) {
exit(1);
} else {
// allow children ptrace parent
#ifdef __linux__
prctl(PR_SET_PTRACER, child_pid, 0, 0, 0);
#endif
// sleep 5s, wait gdb attach
sleep(5);
}
@ -118,7 +122,9 @@ void print_trace() {
exit(0);
} else {
// allow children ptrace parent
#ifdef __linux__
prctl(PR_SET_PTRACER, child_pid, 0, 0, 0);
#endif
waitpid(child_pid,NULL,0);
}
} else {

View File

@ -12,6 +12,7 @@ import jittor as jt
from jittor import LOG
import os
import re
import platform
class TestAsmTuner(unittest.TestCase):
@classmethod
@ -103,6 +104,7 @@ void jittor::FusedOp::jit_run() {
if check_movnt and jt.flags.cc_type == "clang":
assert bo
@unittest.skipIf(platform.system() == 'Darwin', 'will crash on macOS')
def test_asm_tuner(self):
self.check_cc(self.cc_content,True)
self.check_cc(self.cc_content.replace("@begin","233").replace("@end","666"), False)

View File

@ -10,11 +10,19 @@
# ***************************************************************
import unittest
import jittor as jt
import torch
from torch.nn import functional as F
import numpy as np
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
from torch.nn import functional as F
except:
torch = None
skip_this_test = True
@unittest.skipIf(skip_this_test, "No Torch found")
class TestBicubicInterpolate(unittest.TestCase):
# this is for testing bicubic interpolate
def test_bicubic(self):

View File

@ -9,11 +9,18 @@
import unittest
import jittor as jt
import numpy as np
import ctypes
import sys
import torch
from torch.autograd import Variable
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
from torch.autograd import Variable
except:
torch = None
skip_this_test = True
@unittest.skipIf(skip_this_test, "No Torch found")
class TestCumprod(unittest.TestCase):
def test_cumprod_cpu(self):
for i in range(1,6):

View File

@ -12,6 +12,14 @@ import jittor as jt
import numpy as np
import jittor.distributions as jd
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
except:
torch = None
skip_this_test = True
class TestOneHot(unittest.TestCase):
def test_presum(self):
@ -19,6 +27,7 @@ class TestOneHot(unittest.TestCase):
b = jd.simple_presum(a)
assert (b.data == [[0,1,3,6,10]]).all()
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_one_hot(self):
a = jd.OneHotCategorical(jt.array([0.25, 0.25, 0.25, 0.25]))
x = a.sample().numpy()
@ -30,7 +39,7 @@ class TestOneHot(unittest.TestCase):
assert y.shape == [2,3,4]
probs,probs2 = np.random.uniform(0,1,(10)), np.random.uniform(0,1,(10))
probs,probs2 = probs / probs.sum(),probs2 / probs2.sum()
import torch
jc, jc2 = jd.OneHotCategorical(jt.array(probs)),jd.OneHotCategorical(jt.array(probs2))
tc, tc2 = torch.distributions.OneHotCategorical(torch.tensor(probs)),torch.distributions.OneHotCategorical(torch.tensor(probs2))
assert np.allclose(jc.entropy().data,tc.entropy().numpy())
@ -51,8 +60,8 @@ class TestOneHot(unittest.TestCase):
y.sync()
assert y.shape == [2,3]
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_normal(self):
import torch
for _ in range(4):
mu = np.random.uniform(-1,1)
sigma = np.random.uniform(0,2)
@ -67,8 +76,8 @@ class TestOneHot(unittest.TestCase):
tn2 = torch.distributions.Normal(mu2,sigma2)
assert np.allclose(jd.kl_divergence(jn,jn2).data,torch.distributions.kl_divergence(tn,tn2).numpy())
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_categorical1(self):
import torch
for _ in range(4):
probs,probs2 = np.random.uniform(0,1,(10)), np.random.uniform(0,1,(10))
probs,probs2 = probs / probs.sum(),probs2 / probs2.sum()
@ -79,9 +88,9 @@ class TestOneHot(unittest.TestCase):
np.testing.assert_allclose(jc.log_prob(x), tc.log_prob(torch.tensor(x)), atol=1e-5)
assert np.allclose(jd.kl_divergence(jc,jc2),torch.distributions.kl_divergence(tc,tc2))
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_categorical2(self):
def check(prob_shape, sample_shape):
import torch
for _ in range(4):
probs,probs2 = np.random.uniform(0,1,prob_shape), np.random.uniform(0,1, prob_shape)
@ -98,9 +107,9 @@ class TestOneHot(unittest.TestCase):
check((2,3), (4,))
check((3,4,5,6), (2,))
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_one_hot_categorical2(self):
def check(prob_shape, sample_shape):
import torch
for _ in range(4):
probs,probs2 = np.random.uniform(0,1,prob_shape), np.random.uniform(0,1, prob_shape)
@ -117,8 +126,8 @@ class TestOneHot(unittest.TestCase):
check((2,3), (4,))
check((3,4,5,6), (2,))
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_uniform(self):
import torch
for _ in range(4):
low, low2 = np.random.randint(-1,2), np.random.randint(-1,2)
leng, leng2 = np.random.uniform(0,2), np.random.uniform(0,2)
@ -130,8 +139,8 @@ class TestOneHot(unittest.TestCase):
assert np.allclose(ju.log_prob(x),tu.log_prob(torch.tensor(x)))
assert np.allclose(jd.kl_divergence(ju,ju2),torch.distributions.kl_divergence(tu,tu2))
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_geometric(self):
import torch
for _ in range(4):
prob, prob2 = np.random.uniform(0,1), np.random.uniform(0,1)
jg, jg2 = jd.Geometric(prob),jd.Geometric(prob2)

View File

@ -73,9 +73,10 @@ class TestExample(unittest.TestCase):
prev = jt.liveness_info()
print(f"step {i}, loss = {loss_mean.data.sum()} {jt.liveness_info()}")
# result is 0.0009948202641680837
result = 0.0009948202641680837
assert abs(loss_mean.data - result) < 1e-6
possible_results = [0.0009948202641680837, 0.001381353591568768]
loss_mean = loss_mean.data
assert any(abs(loss_mean - r) < 1e-6 for r in possible_results)
jt.clean()
if __name__ == "__main__":

View File

@ -82,8 +82,8 @@ class TestExample(unittest.TestCase):
print(f"step {i}, loss = {loss_mean.data.sum()} {jt.liveness_info()}")
print(all_loss)
result = 19.8639366890402
assert abs(all_loss - result) < 1e-3
possible_results = [19.8639366890402, 8.207454475712439]
assert any(abs(all_loss - r) < 1e-3 for r in possible_results)
jt.clean()
if __name__ == "__main__":

View File

@ -10,11 +10,19 @@
# ***************************************************************
import unittest
import jittor as jt
import torch
from torch.nn import functional as F
import numpy as np
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
from torch.nn import functional as F
except:
torch = None
skip_this_test = True
@unittest.skipIf(skip_this_test, "No Torch Found")
class TestFoldOp(unittest.TestCase):
def test_fold(self):
# test unfold first and the test fold.

View File

@ -8,13 +8,13 @@
# This file is subject to the terms and conditions defined in
# file 'LICENSE.txt', which is part of this source code package.
# ***************************************************************
import torch
from torch.autograd import Variable
import jittor as jt
import numpy as np
import unittest
try:
import torch
from torch.autograd import Variable
import autograd.numpy as anp
from autograd import jacobian

View File

@ -62,7 +62,7 @@ class TestLongestDisFuse(unittest.TestCase):
continue
shape = s.split("[")[1].split("]")[0].split(",")
ptr = s.split("(")[1].split(")")[0].split(",")[-1]
if ptr != '0':
if ptr != '0' and ptr != '0x0':
assert len(shape)<=5, s
if __name__ == "__main__":

View File

@ -157,9 +157,9 @@ class TestMatmul(unittest.TestCase):
loss_mean.data.sum()
jt.liveness_info()
# result is 0.00022486248053610325
result = 0.00022486248053610325
assert abs(loss_mean.data - result) < 1e-6, [loss_mean.data, result]
possible_results = [0.00022486248053610325, 0.00020916158973705024]
loss_mean = loss_mean.data
assert any(abs(loss_mean - r) < 1e-6 for r in possible_results)
jt.clean()
def test_backward_once(self):

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@ -8,6 +8,7 @@ import unittest
import jittor as jt
import os
import numpy as np
import sys
class TestMiscIssue(unittest.TestCase):
def test_issue4(self):
@ -28,7 +29,7 @@ import torch
A = torch.rand(N, N)
torch.matmul(A, A)
"""
assert os.system(f"python3.7 -c '{src}'")==0
assert os.system(f"{sys.executable} -c '{src}'")==0
src = """N = 100
import torch
A = torch.rand(N, N)
@ -40,7 +41,7 @@ b = a.broadcast([N,N,N], dims=[0]) * a.broadcast([N,N,N], dims=[2])
b = b.sum(1)
b.sync()
"""
assert os.system(f"python3.7 -c '{src}'")==0
assert os.system(f"{sys.executable} -c '{src}'")==0
def test_mkl_conflict1(self):
try:
@ -66,7 +67,7 @@ m = torch.nn.Conv2d(3, 4, 5, 1, 2)
m(torch.rand(*nchw))
"""
assert os.system(f"python3.7 -c '{src}'")==0
assert os.system(f"{sys.executable} -c '{src}'")==0
def test_mkl_conflict2(self):
try:
@ -92,7 +93,7 @@ jt.mkl_ops.mkl_conv(x, w, 1, 1, 2, 2).sync()
"""
assert os.system(f"python3.7 -c '{src}'")==0
assert os.system(f"{sys.executable} -c '{src}'")==0
def test_parallel(self):
a = jt.code([4], "int", cpu_src="""

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@ -18,12 +18,14 @@ import unittest
from .test_reorder_tuner import simple_parser
from .test_log import find_log_with_re
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
except:
skip_this_test = True
class TestRandomOp(unittest.TestCase):
@unittest.skipIf(not jt.has_cuda, "Cuda not found")
@jt.flag_scope(use_cuda=1)
@ -51,6 +53,7 @@ class TestRandomOp(unittest.TestCase):
logs = find_log_with_re(raw_log, "(Jit op key (not )?found: " + "curand_random" + ".*)")
assert len(logs)==1
@unittest.skipIf(skip_this_test, "No Torch Found")
def test_normal(self):
from jittor import init
n = 10000

View File

@ -18,12 +18,9 @@ try:
jt.dirty_fix_pytorch_runtime_error()
import torch
import torch.nn as tnn
import torchvision
from torch.autograd import Variable
except:
torch = None
tnn = None
torchvision = None
skip_this_test = True
# TODO: more test

View File

@ -9,11 +9,16 @@
import unittest
import jittor as jt
import numpy as np
import ctypes
import sys
import torch
from torch.autograd import Variable
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
except:
skip_this_test = True
@unittest.skipIf(skip_this_test, "No Torch Found")
class TestSearchsorted(unittest.TestCase):
def test_searchsorted_cpu(self):
for i in range(1,3):

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@ -11,6 +11,7 @@ from jittor import Module
from jittor.models import resnet
import pickle
from PIL import Image
import platform
f32 = jt.float32
@ -148,7 +149,6 @@ class TestTraceVar(unittest.TestCase):
if i not in data["node_data"]:
assert 0, (i, "not found")
def test_resnet_trainx(self):
with jt.flag_scope(trace_py_var=2):

View File

@ -416,7 +416,7 @@ class Tester(unittest.TestCase):
split = img.split()
for i in range(4):
np.testing.assert_allclose(expected_output[:,:,i], transform.to_tensor(split[i])[0])
self.assertTrue(np.allclose(expected_output[:,:,i], transform.to_tensor(split[i])[0]))
img_data = jt.random((4, 4, 4))
expected_output = img_data.multiply(255).int().float().divide(255)

View File

@ -32,7 +32,7 @@ cc_flags = f" -g -O0 -DTEST --std=c++14 -I{jittor_path}/test -I{jittor_path}/src
class TestUtils(unittest.TestCase):
def test_cache_compile(self):
cmd = f"cd {cache_path} && g++ {jittor_path}/src/utils/log.cc {jittor_path}/src/utils/tracer.cc {jittor_path}/src/utils/cache_compile.cc -lpthread {cc_flags} -o cache_compile && cache_path={cache_path} jittor_path={jittor_path} ./cache_compile"
cmd = f"cd {cache_path} && g++ {jittor_path}/src/utils/log.cc {jittor_path}/src/utils/tracer.cc {jittor_path}/src/utils/str_utils.cc {jittor_path}/src/utils/cache_compile.cc -lpthread {cc_flags} -o cache_compile && cache_path={cache_path} jittor_path={jittor_path} ./cache_compile"
self.assertEqual(os.system(cmd), 0)
def test_log(self):

View File

@ -23,6 +23,7 @@ from jittor.compiler import run_cmd
from jittor_utils import translator
from jittor.utils.polish_centos import run_in_centos
import sys
import platform
jittor_path = jt.flags.jittor_path
root_path = os.path.realpath(os.path.join(jt.flags.jittor_path, "..", ".."))
@ -52,7 +53,18 @@ from pathlib import Path
home = str(Path.home())
# for cc_type in ["g++", "clang"]:
# for device in ["cpu", "cuda"]:
for os_name in ['ubuntu', 'centos']:
os_name_system_dict = {
'ubuntu': 'Linux',
'centos': 'Linux',
'macos': 'Darwin',
}
for os_name, os_type in os_name_system_dict.items():
if platform.system() != os_type:
continue
os_arch = platform.machine() if os_type == 'Darwin' else ''
for cc_type in ["g++"]:
for device in ["cpu"]:
key = f"{git_version}-{cc_type}-{device}"
@ -61,13 +73,15 @@ for os_name in ['ubuntu', 'centos']:
env += cname
# use core2 arch, avoid using avx instructions
# TODO: support more archs, such as arm, or use ir(GIMPLE or LLVM)
env += " cc_flags='-march=core2' "
if platform.machine() == "x86_64":
env += " cc_flags='-march=core2' "
if device == "cpu":
env += "nvcc_path='' "
env += " nvcc_path='' "
elif jt.flags.nvcc_path == "":
env = "unset nvcc_path && " + env
cmd = f"{env} {sys.executable} -c 'import jittor'"
if key != 'ubuntu': key += '-' + os_name
if os_arch : key += '-' + os_arch
if os_name == 'centos':
run_in_centos(env)
obj_path = home + f"/.cache/centos/build/{cc_type}/{device}/{cname}/obj_files"

View File

@ -13,12 +13,16 @@ import sys
import inspect
import datetime
import contextlib
import platform
import threading
import time
from ctypes import cdll
import shutil
import urllib.request
if platform.system() == 'Darwin':
mp.set_start_method('fork')
class LogWarper:
def __init__(self):
self.log_silent = int(os.environ.get("log_silent", "0"))
@ -156,6 +160,8 @@ def pool_cleanup():
del p
def pool_initializer():
if cc is None:
try_import_jit_utils_core()
cc.init_subprocess()
def run_cmds(cmds, cache_path, jittor_path, msg="run_cmds"):
@ -163,10 +169,17 @@ def run_cmds(cmds, cache_path, jittor_path, msg="run_cmds"):
bk = mp.current_process()._config.get('daemon')
mp.current_process()._config['daemon'] = False
if pool_size == 0:
mem_bytes = os.sysconf('SC_PAGE_SIZE') * os.sysconf('SC_PHYS_PAGES')
mem_gib = mem_bytes/(1024.**3)
pool_size = min(16,max(int(mem_gib // 3), 1))
LOG.i(f"Total mem: {mem_gib:.2f}GB, using {pool_size} procs for compiling.")
try:
mem_bytes = os.sysconf('SC_PAGE_SIZE') * os.sysconf('SC_PHYS_PAGES')
mem_gib = mem_bytes/(1024.**3)
pool_size = min(16,max(int(mem_gib // 3), 1))
LOG.i(f"Total mem: {mem_gib:.2f}GB, using {pool_size} procs for compiling.")
except ValueError:
# On macOS, python with version lower than 3.9 do not support SC_PHYS_PAGES.
# Use hard coded pool size instead.
pool_size = 4
LOG.i(f"using {pool_size} procs for compiling.")
p = Pool(pool_size, initializer=pool_initializer)
p.__enter__()
import atexit
@ -215,7 +228,7 @@ def find_cache_path():
for name in cache_name.split("/"):
dirs.insert(-1, name)
os.environ["cache_name"] = cache_name
LOG.v("cache_name", cache_name)
LOG.v("cache_name: ", cache_name)
for d in dirs:
path = os.path.join(path, d)
if not os.path.isdir(path):
@ -237,7 +250,10 @@ def get_version(output):
if len(v) == 0:
v = re.findall("[0-9]+\\.[0-9]+", version)
assert len(v) != 0, f"Can not find version number from: {version}"
version = "("+v[-1]+")"
if 'clang' in version and platform.system() == 'Darwin':
version = "("+v[-3]+")"
else:
version = "("+v[-1]+")"
return version
def get_int_version(output):
@ -286,10 +302,21 @@ cc_type = get_cc_type(cc_path)
cache_path = find_cache_path()
# Search python3.x-config
# Note:
# This may be called via c++ console. In that case, sys.executable will
# be a path to the executable file, rather than python. So, we cannot infer
# python-config path only from sys.executable.
# To address this issue, we add predefined paths to search,
# - Linux: /usr/bin/python3.x-config
# - macOS (installed via homebrew): /usr/local/bin/python3.x-config
# There may be issues under other cases, e.g., installed via conda.
py3_config_paths = [
os.path.dirname(sys.executable) + f"/python3.{sys.version_info.minor}-config",
sys.executable + "-config",
f"/usr/bin/python3.{sys.version_info.minor}-config",
f"/usr/local/bin/python3.{sys.version_info.minor}-config",
f'/opt/homebrew/bin/python3.{sys.version_info.minor}-config',
os.path.dirname(sys.executable) + "/python3-config",
]
if "python_config_path" in os.environ:
@ -302,4 +329,4 @@ else:
raise RuntimeError(f"python3.{sys.version_info.minor}-config "
f"not found in {py3_config_paths}, please specify "
f"enviroment variable 'python_config_path',"
f" or apt install python3.{sys.version_info.minor}-dev")
f" or install python3.{sys.version_info.minor}-dev")

View File

@ -1,4 +1,5 @@
import os
import platform
import sys
import jittor_utils
from jittor_utils import LOG
@ -27,10 +28,20 @@ if __name__ == "__main__":
s += " -I"+os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "jittor", "src"))
s += " "
elif arg == "--libs-flags":
libbase = "/usr/lib/x86_64-linux-gnu"
libpath = libbase + f"/lib{base}.so"
assert os.path.isfile(libpath), f"lib not exist: {libpath}"
s += f" -L{libbase} -l{base} -ldl "
libext = {
'Linux': 'so',
'Darwin': 'dylib',
'Windows': 'DLL',
}[platform.system()]
ldflags = jittor_utils.run_cmd(jittor_utils.py3_config_path + " --ldflags")
libpaths = [l[2:] for l in ldflags.split(' ') if l.startswith("-L")]
for libbase in libpaths:
libpath = os.path.join(libbase, f"lib{base}.{libext}")
if os.path.isfile(libpath):
s += f" -L{libbase} -l{base} -ldl "
break
else:
raise RuntimeError("Python dynamic library not found")
elif arg == "--cxx-flags":
s += " --std=c++17 "
elif arg == "--cxx-example":

View File

@ -1,13 +1,13 @@
error_msg = """Jittor only supports Ubuntu>=16.04 currently.
error_msg = """Jittor only supports Linux and macOS currently.
For other OS, use Jittor may be risky.
If you insist on installing, please set the environment variable : export FORCE_INSTALL=1
We strongly recommended docker installation:
We strongly recommend docker installation:
# CPU only(Linux)
# CPU only (Linux)
>>> docker run -it --network host jittor/jittor
# CPU and CUDA(Linux)
# CPU and CUDA (Linux)
>>> docker run -it --network host jittor/jittor-cuda
# CPU only(Mac and Windows)
# CPU only (Mac and Windows)
>>> docker run -it -p 8888:8888 jittor/jittor
Reference:
@ -15,19 +15,10 @@ Reference:
"""
from warnings import warn
import os
try:
with open("/etc/os-release", "r", encoding='utf8') as f:
s = f.read().splitlines()
m = {}
for line in s:
a = line.split('=')
if len(a) != 2: continue
m[a[0]] = a[1].replace("\"", "")
# assert m["NAME"] == "Ubuntu" and float(m["VERSION_ID"].split('.')[0])>=16, error_msg
except Exception as e:
print(e)
warn(error_msg)
if os.environ.get("FORCE_INSTALL", '0') != '1': raise
import platform
if not platform.system() in ['Linux', 'Darwin']:
assert os.environ.get("FORCE_INSTALL", '0') != '1', error_msg
import setuptools
from setuptools import setup, find_packages