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update setup and workflow (#222)

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ver217 2022-02-14 17:09:30 +08:00 committed by Frank Lee
parent 3a1a9820b0
commit 578ea0583b
5 changed files with 159 additions and 129 deletions
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2
.github/workflows/PR_CI.yml vendored
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@ -43,7 +43,7 @@ jobs:
- name: Install Colossal-AI - name: Install Colossal-AI
run: | run: |
pip install -r requirements/requirements.txt pip install -r requirements/requirements.txt
pip install -v --no-cache-dir --global-option="--cuda_ext" . pip install -v --no-cache-dir .
- name: Unit Testing - name: Unit Testing
run: | run: |
pytest tests pytest tests

32
README.md
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@ -17,9 +17,26 @@ An integrated large-scale model training system with efficient parallelization t
## Installation ## Installation
### Install From Source (Recommended) ### PyPI
> We **recommend** you to install from source as the Colossal-AI is updating frequently in the early versions. The documentation will be in line with the main branch of the repository. Feel free to raise an issue if you encounter any problem. :) ```bash
pip install colossalai
```
This command will install CUDA extension if your have installed CUDA, NVCC and torch.
If you don't want to install CUDA extension, you should add `--global-option="--no_cuda_ext"`, like:
```bash
pip install colossalai --global-option="--no_cuda_ext"
```
If you want to use `ZeRO`, you can run:
```bash
pip install colossalai[zero]
```
### Install From Source
> The documentation will be in line with the main branch of the repository. Feel free to raise an issue if you encounter any problem. :)
```shell ```shell
git clone https://github.com/hpcaitech/ColossalAI.git git clone https://github.com/hpcaitech/ColossalAI.git
@ -31,19 +48,12 @@ pip install -r requirements/requirements.txt
pip install . pip install .
``` ```
Install and enable CUDA kernel fusion (compulsory installation when using fused optimizer) If you don't want to install and enable CUDA kernel fusion (compulsory installation when using fused optimizer):
```shell ```shell
pip install -v --no-cache-dir --global-option="--cuda_ext" . pip install --global-option="--no_cuda_ext" .
``` ```
### PyPI
```bash
pip install colossalai
```
## Use Docker ## Use Docker
Run the following command to build a docker image from Dockerfile provided. Run the following command to build a docker image from Dockerfile provided.

2
docker/Dockerfile
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@ -8,4 +8,4 @@ RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple \
# install colossalai # install colossalai
RUN git clone https://github.com/hpcaitech/ColossalAI.git \ RUN git clone https://github.com/hpcaitech/ColossalAI.git \
&& cd ./ColossalAI \ && cd ./ColossalAI \
&& pip install -v --no-cache-dir --global-option="--cuda_ext" . && pip install -v --no-cache-dir .

1
requirements/requirements-zero.txt Normal file
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@ -0,0 +1 @@
deepspeed

251
setup.py
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@ -2,12 +2,16 @@ import os
import subprocess import subprocess
import sys import sys
import torch from setuptools import find_packages, setup
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
# ninja build does not work unless include_dirs are abs path # ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__)) this_dir = os.path.dirname(os.path.abspath(__file__))
build_cuda_ext = True
ext_modules = []
if '--no_cuda_ext' in sys.argv:
sys.argv.remove('--no_cuda_ext')
build_cuda_ext = False
def get_cuda_bare_metal_version(cuda_dir): def get_cuda_bare_metal_version(cuda_dir):
@ -29,13 +33,45 @@ def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
print("\nCompiling cuda extensions with") print("\nCompiling cuda extensions with")
print(raw_output + "from " + cuda_dir + "/bin\n") print(raw_output + "from " + cuda_dir + "/bin\n")
if (bare_metal_major != torch_binary_major) or (bare_metal_minor != torch_binary_minor): if bare_metal_major != torch_binary_major:
raise RuntimeError("Cuda extensions are being compiled with a version of Cuda that does " + print(
"not match the version used to compile Pytorch binaries. " + f'The detected CUDA version ({raw_output}) mismatches the version that was used to compile PyTorch ({torch.version.cuda}). CUDA extension will not be installed.')
"Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda) + return False
"In some cases, a minor-version mismatch will not cause later errors: " +
"https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. " if bare_metal_minor != torch_binary_minor:
"You can try commenting out this check (at your own risk).") print("\nWarning: Cuda extensions are being compiled with a version of Cuda that does "
+ "not match the version used to compile Pytorch binaries. "
+ "Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda)
+ "In some cases, a minor-version mismatch will not cause later errors: "
+ "https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. ")
return True
def check_cuda_availability(cuda_dir):
if not torch.cuda.is_available():
# https://github.com/NVIDIA/apex/issues/486
# Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query torch.cuda.get_device_capability(),
# which will fail if you are compiling in an environment without visible GPUs (e.g. during an nvidia-docker build command).
print('\nWarning: Torch did not find available GPUs on this system.\n',
'If your intention is to cross-compile, this is not an error.\n'
'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n'
'Volta (compute capability 7.0), Turing (compute capability 7.5),\n'
'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
'If you wish to cross-compile for a single specific architecture,\n'
'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
_, bare_metal_major, _ = get_cuda_bare_metal_version(cuda_dir)
if int(bare_metal_major) == 11:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0"
else:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
return False
if cuda_dir is None:
print(
"nvcc was not found. CUDA extension will not be installed. If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
return False
return True
def append_nvcc_threads(nvcc_extra_args): def append_nvcc_threads(nvcc_extra_args):
@ -50,118 +86,98 @@ def fetch_requirements(path):
return [r.strip() for r in fd.readlines()] return [r.strip() for r in fd.readlines()]
if not torch.cuda.is_available(): if build_cuda_ext:
# https://github.com/NVIDIA/apex/issues/486 try:
# Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query torch.cuda.get_device_capability(), import torch
# which will fail if you are compiling in an environment without visible GPUs (e.g. during an nvidia-docker build command). from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension,
print('\nWarning: Torch did not find available GPUs on this system.\n', CUDAExtension)
'If your intention is to cross-compile, this is not an error.\n' print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__))
'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n' TORCH_MAJOR = int(torch.__version__.split('.')[0])
'Volta (compute capability 7.0), Turing (compute capability 7.5),\n' TORCH_MINOR = int(torch.__version__.split('.')[1])
'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
'If you wish to cross-compile for a single specific architecture,\n'
'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) == 11:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0"
else:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__)) if TORCH_MAJOR < 1 or (TORCH_MAJOR == 1 and TORCH_MINOR < 8):
TORCH_MAJOR = int(torch.__version__.split('.')[0]) raise RuntimeError("Colossal-AI requires Pytorch 1.8 or newer.\n"
TORCH_MINOR = int(torch.__version__.split('.')[1]) + "The latest stable release can be obtained from https://pytorch.org/")
except ImportError:
print('torch is not found. CUDA extension will not be installed')
build_cuda_ext = False
if TORCH_MAJOR < 1 or (TORCH_MAJOR == 1 and TORCH_MINOR < 8): if build_cuda_ext:
raise RuntimeError("Colossal-AI requires Pytorch 1.8 or newer.\n" + build_cuda_ext = check_cuda_availability(CUDA_HOME) and check_cuda_torch_binary_vs_bare_metal(CUDA_HOME)
"The latest stable release can be obtained from https://pytorch.org/")
cmdclass = {}
ext_modules = []
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
# and
# https://github.com/NVIDIA/apex/issues/456
# https://github.com/pytorch/pytorch/commit/eb7b39e02f7d75c26d8a795ea8c7fd911334da7e#diff-4632522f237f1e4e728cb824300403ac
version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
if "--cuda_ext" in sys.argv:
sys.argv.remove("--cuda_ext")
if CUDA_HOME is None:
raise RuntimeError(
"--cuda_ext was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
else:
check_cuda_torch_binary_vs_bare_metal(CUDA_HOME)
def cuda_ext_helper(name, sources, extra_cuda_flags):
return CUDAExtension(name=name,
sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in sources],
include_dirs=[os.path.join(
this_dir, 'colossalai/kernel/cuda_native/csrc/kernels/include')],
extra_compile_args={'cxx': ['-O3'] + version_dependent_macros,
'nvcc': append_nvcc_threads(['-O3',
'--use_fast_math'] + version_dependent_macros + extra_cuda_flags)})
ext_modules.append(cuda_ext_helper('colossal_C',
['colossal_C_frontend.cpp',
'multi_tensor_sgd_kernel.cu',
'multi_tensor_scale_kernel.cu',
'multi_tensor_adam.cu',
'multi_tensor_l2norm_kernel.cu',
'multi_tensor_lamb.cu'],
['-lineinfo']))
cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) >= 11:
cc_flag.append('-gencode')
cc_flag.append('arch=compute_80,code=sm_80')
extra_cuda_flags = ['-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda']
ext_modules.append(cuda_ext_helper('colossal_scaled_upper_triang_masked_softmax',
['scaled_upper_triang_masked_softmax.cpp',
'scaled_upper_triang_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('colossal_scaled_masked_softmax',
['scaled_masked_softmax.cpp', 'scaled_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-maxrregcount=50']
ext_modules.append(cuda_ext_helper('colossal_layer_norm_cuda',
['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu'],
extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-std=c++14',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_HALF2_OPERATORS__',
'-DTHRUST_IGNORE_CUB_VERSION_CHECK']
ext_modules.append(cuda_ext_helper('colossal_multihead_attention',
['multihead_attention_1d.cpp',
'kernels/cublas_wrappers.cu',
'kernels/transform_kernels.cu',
'kernels/dropout_kernels.cu',
'kernels/normalize_kernels.cu',
'kernels/softmax_kernels.cu',
'kernels/general_kernels.cu',
'kernels/cuda_util.cu'],
extra_cuda_flags + cc_flag))
install_requires = fetch_requirements('requirements/requirements.txt') if build_cuda_ext:
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
# and
# https://github.com/NVIDIA/apex/issues/456
# https://github.com/pytorch/pytorch/commit/eb7b39e02f7d75c26d8a795ea8c7fd911334da7e#diff-4632522f237f1e4e728cb824300403ac
version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5']
def cuda_ext_helper(name, sources, extra_cuda_flags):
return CUDAExtension(name=name,
sources=[os.path.join('colossalai/kernel/cuda_native/csrc', path) for path in sources],
include_dirs=[os.path.join(
this_dir, 'colossalai/kernel/cuda_native/csrc/kernels/include')],
extra_compile_args={'cxx': ['-O3'] + version_dependent_macros,
'nvcc': append_nvcc_threads(['-O3',
'--use_fast_math'] + version_dependent_macros + extra_cuda_flags)})
ext_modules.append(cuda_ext_helper('colossal_C',
['colossal_C_frontend.cpp',
'multi_tensor_sgd_kernel.cu',
'multi_tensor_scale_kernel.cu',
'multi_tensor_adam.cu',
'multi_tensor_l2norm_kernel.cu',
'multi_tensor_lamb.cu'],
['-lineinfo']))
cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) >= 11:
cc_flag.append('-gencode')
cc_flag.append('arch=compute_80,code=sm_80')
extra_cuda_flags = ['-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda']
ext_modules.append(cuda_ext_helper('colossal_scaled_upper_triang_masked_softmax',
['scaled_upper_triang_masked_softmax.cpp',
'scaled_upper_triang_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('colossal_scaled_masked_softmax',
['scaled_masked_softmax.cpp', 'scaled_masked_softmax_cuda.cu'],
extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-maxrregcount=50']
ext_modules.append(cuda_ext_helper('colossal_layer_norm_cuda',
['layer_norm_cuda.cpp', 'layer_norm_cuda_kernel.cu'],
extra_cuda_flags + cc_flag))
extra_cuda_flags = ['-std=c++14',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_HALF2_OPERATORS__',
'-DTHRUST_IGNORE_CUB_VERSION_CHECK']
ext_modules.append(cuda_ext_helper('colossal_multihead_attention',
['multihead_attention_1d.cpp',
'kernels/cublas_wrappers.cu',
'kernels/transform_kernels.cu',
'kernels/dropout_kernels.cu',
'kernels/normalize_kernels.cu',
'kernels/softmax_kernels.cu',
'kernels/general_kernels.cu',
'kernels/cuda_util.cu'],
extra_cuda_flags + cc_flag))
setup( setup(
name='colossalai', name='colossalai',
version='0.0.1-beta', version='0.0.2',
packages=find_packages(exclude=('benchmark', packages=find_packages(exclude=('benchmark',
'docker', 'docker',
'tests', 'tests',
@ -174,5 +190,8 @@ setup(
description='An integrated large-scale model training system with efficient parallelization techniques', description='An integrated large-scale model training system with efficient parallelization techniques',
ext_modules=ext_modules, ext_modules=ext_modules,
cmdclass={'build_ext': BuildExtension} if ext_modules else {}, cmdclass={'build_ext': BuildExtension} if ext_modules else {},
install_requires=install_requires, install_requires=fetch_requirements('requirements/requirements.txt'),
extras_require={
'zero': fetch_requirements('requirements/requirements-zero.txt'),
}
) )