mirror of https://github.com/Jittor/Jittor
commit
ae2eafd878
|
@ -1,5 +1,6 @@
|
|||
my
|
||||
.refresh
|
||||
.DS_Store
|
||||
__pycache__
|
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.ipynb_checkpoints/
|
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.vscode/
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||||
|
|
28
README.cn.md
28
README.cn.md
|
@ -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 Linux(WSL)**
|
||||
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**(x86_64)或 **Windows Subsystem of Linux(WSL)**
|
||||
* 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2:macOS 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:docker,pip和手动安装:
|
||||
|
||||
|
@ -112,6 +114,7 @@ Jittor 提供了三种安装方法:docker,pip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
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|||
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` 和 `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
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```
|
||||
|
||||
目前在macOS中,jittor 只支持 CPU 计算。
|
||||
|
||||
|
||||
## 手动安装
|
||||
|
||||
|
||||
|
|
28
README.md
28
README.md
|
@ -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.
|
||||
|
|
|
@ -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 Linux(WSL)**
|
||||
* 操作系统: **Linux**(e.g. Ubuntu/CentOS/Arch), **macOS**(x86_64)或 **Windows Subsystem of Linux(WSL)**
|
||||
* 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2:macOS 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:docker,pip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` 和 `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
|
||||
|
||||
|
|
|
@ -1169,9 +1169,11 @@ def dirty_fix_pytorch_runtime_error():
|
|||
jt.dirty_fix_pytorch_runtime_error()
|
||||
import torch
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'''
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import os
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os.RTLD_GLOBAL = os.RTLD_GLOBAL | os.RTLD_DEEPBIND
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import os, platform
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|
||||
if platform.system() == 'Linux':
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os.RTLD_GLOBAL = os.RTLD_GLOBAL | os.RTLD_DEEPBIND
|
||||
|
||||
|
||||
import atexit
|
||||
|
||||
|
|
|
@ -5,6 +5,7 @@
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|||
# file 'LICENSE.txt', which is part of this source code package.
|
||||
# ***************************************************************
|
||||
import os, sys, shutil
|
||||
import platform
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||||
from .compiler import *
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||||
from jittor_utils import run_cmd, get_version, get_int_version
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||||
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")
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||||
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")
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# mkl_path decouple with cc_path
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||||
from pathlib import Path
|
||||
mkl_path = os.path.join(str(Path.home()), ".cache", "jittor", "mkl")
|
||||
|
||||
make_cache_dir(mkl_path)
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install_mkl(mkl_path)
|
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mkl_home = ""
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||||
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!=""
|
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if platform.system() == 'Linux':
|
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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)))
|
||||
|
||||
|
||||
|
|
|
@ -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':
|
||||
|
|
|
@ -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 = []
|
||||
|
|
|
@ -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);
|
||||
|
|
|
@ -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;
|
||||
}
|
||||
|
||||
|
|
|
@ -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);
|
||||
|
|
|
@ -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);
|
||||
}
|
||||
|
||||
|
|
|
@ -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;
|
||||
|
|
|
@ -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"
|
||||
|
||||
|
|
|
@ -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 {
|
||||
|
|
|
@ -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;
|
||||
|
|
|
@ -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);
|
||||
}
|
||||
|
||||
|
|
|
@ -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 {
|
||||
|
|
|
@ -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);
|
||||
}
|
||||
|
|
|
@ -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
|
|
@ -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();
|
||||
|
|
|
@ -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(
|
||||
|
|
|
@ -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(
|
||||
|
|
|
@ -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(
|
||||
|
|
|
@ -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() {
|
||||
|
|
|
@ -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];
|
||||
|
|
|
@ -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(
|
||||
|
|
|
@ -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;
|
||||
|
|
|
@ -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 {
|
||||
|
|
|
@ -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)
|
||||
|
|
|
@ -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):
|
||||
|
|
|
@ -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):
|
||||
|
|
|
@ -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)
|
||||
|
|
|
@ -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__":
|
||||
|
|
|
@ -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__":
|
||||
|
|
|
@ -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.
|
||||
|
|
|
@ -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
|
||||
|
||||
|
|
|
@ -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__":
|
||||
|
|
|
@ -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):
|
||||
|
|
|
@ -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="""
|
||||
|
|
|
@ -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
|
||||
|
|
|
@ -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
|
||||
|
|
|
@ -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):
|
||||
|
|
|
@ -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):
|
||||
|
||||
|
|
|
@ -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)
|
||||
|
|
|
@ -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):
|
||||
|
|
|
@ -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"
|
||||
|
|
|
@ -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")
|
||||
|
|
|
@ -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":
|
||||
|
|
27
setup.py
27
setup.py
|
@ -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
|
||||
|
|
Loading…
Reference in New Issue