def install_cutt(root_folder):
# Modified from: https://github.com/ap-hynninen/cutt
url = "https://github.com/Jittor/cutt/archive/master.zip"
filename = "cutt-master.zip"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".zip", ""))
true_md5 = "a6f4f7f75310a69b131e21f1ebec768a"
if os.path.exists(fullname):
md5 = run_cmd('md5sum ' + fullname).split()[0]
if md5 != true_md5:
os.remove(fullname)
shutil.rmtree(dirname)
if not os.path.isfile(os.path.join(dirname, "bin", "cutt_test")):
LOG.i("Downloading cutt...")
download_url_to_local(url, filename, root_folder, true_md5)
import zipfile
zf = zipfile.ZipFile(fullname)
try:
zf.extractall(path=root_folder)
except RuntimeError as e:
print(e)
raise
zf.close()
LOG.i("installing cutt...")
run_cmd(f"make", cwd=dirname)
return dirname
def safeunpickle(path):
if path.startswith("jittorhub://"):
path = path.replace(
"jittorhub://",
"https://cg.cs.tsinghua.edu.cn/jittor/assets/build/checkpoints/")
if path.startswith("https:") or path.startswith("http:"):
base = path.split("/")[-1]
fname = os.path.join(compiler.ck_path, base)
from jittor.utils.misc import download_url_to_local
download_url_to_local(path, base, compiler.ck_path, None)
path = fname
if path.endswith(".pth"):
try:
dirty_fix_pytorch_runtime_error()
import torch
except:
raise RuntimeError(
"pytorch need to be installed when load pth format.")
model_dict = torch.load(path, map_location=torch.device('cpu'))
return model_dict
with open(path, "rb") as f:
s = f.read()
if not s.endswith(b"HCAJSLHD"):
return pickle.loads(s)
checksum = s[-28:-8]
s = s[:-28]
if hashlib.sha1(s).digest() != checksum:
raise ValueError("Pickle checksum does not match! path: " + path)
return pickle.loads(s)
def install_nccl(root_folder):
url = "https://github.com/NVIDIA/nccl/archive/v2.6.4-1.tar.gz"
filename = "nccl.tgz"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, "nccl-2.6.4-1")
true_md5 = "38d7a9e98d95a99df0a4f1ad6fb50fa7"
if os.path.exists(fullname):
md5 = run_cmd('md5sum '+fullname).split()[0]
if md5 != true_md5:
os.remove(fullname)
if os.path.isdir(dirname):
shutil.rmtree(dirname)
if not os.path.isfile(os.path.join(dirname, "build", "lib", "libnccl.so")):
LOG.i("Downloading nccl...")
download_url_to_local(url, filename, root_folder, true_md5)
if core.get_device_count() == 0:
return
if not inside_mpi():
return
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
LOG.i("installing nccl...")
arch_flag = f" -arch={','.join(map(lambda x:'sm_'+str(x),flags.cuda_archs))} "
run_cmd(f"make -j8 src.build CUDA_HOME='{cuda_home}' NVCC_GENCODE='{arch_flag}' ", cwd=dirname)
return dirname
def install_nccl(root_folder):
url = "https://github.com/NVIDIA/nccl/archive/v2.8.4-1.tar.gz"
url = "https://codeload.github.com/NVIDIA/nccl/tar.gz/v2.8.4-1"
filename = "nccl.tgz"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, "nccl-2.8.4-1")
true_md5 = "900666558c5bc43e0a5e84045b88a06f"
if os.path.exists(fullname):
md5 = run_cmd('md5sum '+fullname).split()[0]
if md5 != true_md5:
os.remove(fullname)
if os.path.isdir(dirname):
shutil.rmtree(dirname)
if not os.path.isfile(os.path.join(dirname, "build", "lib", "libnccl.so")):
LOG.i("Downloading nccl...")
download_url_to_local(url, filename, root_folder, true_md5)
if core.get_device_count() == 0:
return
if not inside_mpi():
return
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
LOG.i("installing nccl...")
arch_flag = ""
if len(flags.cuda_archs):
arch_flag = f" -arch=compute_{min(flags.cuda_archs)} "
arch_flag += ''.join(map(lambda x:f' -code=sm_{x} ', flags.cuda_archs))
run_cmd(f"make -j8 src.build CUDA_HOME='{cuda_home}' NVCC_GENCODE='{arch_flag}' ", cwd=dirname)
return dirname
def install_cutt(root_folder):
# Modified from: https://github.com/ap-hynninen/cutt
url = "https://codeload.github.com/Jittor/cutt/zip/v1.1"
filename = "cutt-1.1.zip"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".zip",""))
true_md5 = "7bb71cf7c49dbe57772539bf043778f7"
if os.path.exists(fullname):
md5 = run_cmd('md5sum '+fullname).split()[0]
if md5 != true_md5:
os.remove(fullname)
shutil.rmtree(dirname)
if not os.path.isfile(os.path.join(dirname, "bin", "cutt_test")):
LOG.i("Downloading cutt...")
download_url_to_local(url, filename, root_folder, true_md5)
import zipfile
zf = zipfile.ZipFile(fullname)
try:
zf.extractall(path=root_folder)
except RuntimeError as e:
print(e)
raise
zf.close()
LOG.i("installing cutt...")
arch_flag = ""
if len(flags.cuda_archs):
arch_flag = f" -arch=compute_{min(flags.cuda_archs)} "
arch_flag += ''.join(map(lambda x:f' -code=sm_{x} ', flags.cuda_archs))
run_cmd(f"make NVCC_GENCODE='{arch_flag}' nvcc_path='{nvcc_path}'", cwd=dirname)
return dirname
def download(self):
import tarfile
download_url_to_local(self.url, self.filename, self.root, self.tgz_md5)
# extract file
cwd = os.getcwd()
tar = tarfile.open(os.path.join(self.root, self.filename), "r:gz")
os.chdir(self.root)
tar.extractall()
tar.close()
os.chdir(cwd)
def download_url(self):
resources = [
("http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz",
"f68b3c2dcbeaaa9fbdd348bbdeb94873"),
("http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz",
"d53e105ee54ea40749a09fcbcd1e9432"),
("http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz",
"9fb629c4189551a2d022fa330f9573f3"),
("http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz",
"ec29112dd5afa0611ce80d1b7f02629c")
]
for url, md5 in resources:
filename = url.rpartition('/')[2]
download_url_to_local(url, filename, self.data_root, md5)
def install_mkl(root_folder):
url = "https://github.com/intel/mkl-dnn/releases/download/v1.0.2/mkldnn_lnx_1.0.2_cpu_gomp.tgz"
filename = "mkldnn_lnx_1.0.2_cpu_gomp.tgz"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".tgz",""))
if not os.path.isfile(os.path.join(dirname, "examples", "test")):
LOG.i("Downloading mkl...")
download_url_to_local(url, filename, root_folder, "47187284ede27ad3bd64b5f0e7d5e730")
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
assert 0 == os.system(f"cd {dirname}/examples && "
f"{cc_path} -std=c++14 cpu_cnn_inference_f32.cpp -Ofast -lmkldnn -I ../include -L ../lib -o test && LD_LIBRARY_PATH=../lib/ ./test")
def install_cub(root_folder):
url = "https://github.com/NVlabs/cub/archive/v1.8.0.tar.gz"
filename = "cub-1.8.0.tgz"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".tgz",""))
if not os.path.isfile(os.path.join(dirname, "examples", "test")):
LOG.i("Downloading cub...")
download_url_to_local(url, filename, root_folder, "9203ea2499b56782601fddf8a12e9b08")
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
assert 0 == os.system(f"cd {dirname}/examples && "
f"{nvcc_path} device/example_device_radix_sort.cu -O2 -I.. -o test")
if core.get_device_count():
assert 0 == os.system(f"cd {dirname}/examples && ./test")
return dirname
def download_url(self):
'''
Download mnist data set function, this function will be called when download is True.
'''
resources = [
("https://storage.googleapis.com/cvdf-datasets/mnist/train-images-idx3-ubyte.gz",
"f68b3c2dcbeaaa9fbdd348bbdeb94873"),
("https://storage.googleapis.com/cvdf-datasets/mnist/train-labels-idx1-ubyte.gz",
"d53e105ee54ea40749a09fcbcd1e9432"),
("https://storage.googleapis.com/cvdf-datasets/mnist/t10k-images-idx3-ubyte.gz",
"9fb629c4189551a2d022fa330f9573f3"),
("https://storage.googleapis.com/cvdf-datasets/mnist/t10k-labels-idx1-ubyte.gz",
"ec29112dd5afa0611ce80d1b7f02629c")
]
for url, md5 in resources:
filename = url.rpartition('/')[2]
download_url_to_local(url, filename, self.data_root, md5)
def safeunpickle(path):
if path.startswith("jittorhub://"):
path = path.replace(
"jittorhub://",
"https://cg.cs.tsinghua.edu.cn/jittor/assets/build/checkpoints/")
if path.startswith("https:") or path.startswith("http:"):
base = path.split("/")[-1]
fname = os.path.join(compiler.ck_path, base)
from jittor.utils.misc import download_url_to_local
download_url_to_local(path, base, compiler.ck_path, None)
path = fname
with open(path, "rb") as f:
s = f.read()
if not s.endswith(b"HCAJSLHD"):
return pickle.loads(s)
checksum = s[-28:-8]
s = s[:-28]
if hashlib.sha1(s).digest() != checksum:
raise ValueError("Pickle checksum does not match! path: " + path)
return pickle.loads(s)
def install_cub(root_folder):
url = "https://github.com/NVIDIA/cub/archive/1.11.0.tar.gz"
url = "https://codeload.github.com/NVIDIA/cub/tar.gz/1.11.0"
filename = "cub-1.11.0.tgz"
md5 = "97196a885598e40592100e1caaf3d5ea"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".tgz",""))
if not os.path.isfile(os.path.join(dirname, "examples", "test")):
LOG.i("Downloading cub...")
download_url_to_local(url, filename, root_folder, md5)
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
assert 0 == os.system(f"cd {dirname}/examples && "
f"{nvcc_path} device/example_device_radix_sort.cu -O2 -I.. -std=c++14 -o test")
if core.get_device_count():
assert 0 == os.system(f"cd {dirname}/examples && ./test")
return dirname
def install_mkl(root_folder):
# origin url is
# url = "https://github.com/intel/mkl-dnn/releases/download/v1.0.2/mkldnn_lnx_1.0.2_cpu_gomp.tgz"
url = "https://cloud.tsinghua.edu.cn/f/da02bf62b55b4aa3b8ee/?dl=1"
filename = "mkldnn_lnx_1.0.2_cpu_gomp.tgz"
# newest version for oneDNN
# url = "https://github.com/oneapi-src/oneDNN/releases/download/v2.2/dnnl_lnx_2.2.0_cpu_gomp.tgz"
# filename = "dnnl_lnx_2.2.0_cpu_gomp.tgz"
fullname = os.path.join(root_folder, filename)
dirname = os.path.join(root_folder, filename.replace(".tgz",""))
if not os.path.isfile(os.path.join(dirname, "examples", "test")):
LOG.i("Downloading mkl...")
download_url_to_local(url, filename, root_folder, "47187284ede27ad3bd64b5f0e7d5e730")
# newest version for oneDNN
# download_url_to_local(url, filename, root_folder, "35bbbdf550a9d8ad54db798e372000f6")
import tarfile
with tarfile.open(fullname, "r") as tar:
tar.extractall(root_folder)
assert 0 == os.system(f"cd {dirname}/examples && "
f"{cc_path} -std=c++14 cpu_cnn_inference_f32.cpp -Ofast -lmkldnn -I ../include -L ../lib -o test && LD_LIBRARY_PATH=../lib/ ./test")
