def generate_code(ninja_global=None,
declarations_path=None,
nn_path=None,
install_dir=None):
# cwrap depends on pyyaml, so we can't import it earlier
root = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.insert(0, root)
from tools.autograd.gen_autograd import gen_autograd
from tools.jit.gen_jit_dispatch import gen_jit_dispatch
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
# Build THNN/THCUNN.cwrap and then THNN/THCUNN.cpp. These are primarily
# used by the legacy NN bindings.
generate_nn_wrappers(nn_path, install_dir, 'tools/cwrap/plugins/templates')
# Build ATen based Variable classes
autograd_gen_dir = install_dir or 'torch/csrc/autograd/generated'
jit_gen_dir = install_dir or 'torch/csrc/jit/generated'
for d in (autograd_gen_dir, jit_gen_dir):
if not os.path.exists(d):
os.makedirs(d)
gen_autograd(declarations_path or DECLARATIONS_PATH, autograd_gen_dir,
'tools/autograd')
gen_jit_dispatch(declarations_path or DECLARATIONS_PATH, jit_gen_dir,
'tools/jit/templates')
def build_libs(libs):
for lib in libs:
assert lib in dep_libs, 'invalid lib: {}'.format(lib)
if IS_WINDOWS:
build_libs_cmd = ['torch\\lib\\build_libs.bat']
else:
build_libs_cmd = ['bash', 'torch/lib/build_libs.sh']
my_env = os.environ.copy()
my_env["PYTORCH_PYTHON"] = sys.executable
if not IS_WINDOWS:
if WITH_NINJA:
my_env["CMAKE_GENERATOR"] = '-GNinja'
my_env["CMAKE_INSTALL"] = 'ninja install'
else:
my_env['CMAKE_GENERATOR'] = ''
my_env['CMAKE_INSTALL'] = 'make install'
if WITH_SYSTEM_NCCL:
my_env["NCCL_ROOT_DIR"] = NCCL_ROOT_DIR
if WITH_CUDA:
my_env["CUDA_BIN_PATH"] = CUDA_HOME
build_libs_cmd += ['--with-cuda']
if WITH_CUDNN:
my_env["CUDNN_LIB_DIR"] = CUDNN_LIB_DIR
my_env["CUDNN_INCLUDE_DIR"] = CUDNN_INCLUDE_DIR
if subprocess.call(build_libs_cmd + libs, env=my_env) != 0:
sys.exit(1)
if 'ATen' in libs:
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
generate_nn_wrappers()
def build_libs(libs):
for lib in libs:
assert lib in dep_libs, 'invalid lib: {}'.format(lib)
if IS_WINDOWS:
build_libs_cmd = ['torch\\lib\\build_libs.bat']
else:
build_libs_cmd = ['bash', 'torch/lib/build_libs.sh']
my_env = os.environ.copy()
my_env["PYTORCH_PYTHON"] = sys.executable
if not IS_WINDOWS:
if WITH_NINJA:
my_env["CMAKE_GENERATOR"] = '-GNinja'
my_env["CMAKE_INSTALL"] = 'ninja install'
else:
my_env['CMAKE_GENERATOR'] = ''
my_env['CMAKE_INSTALL'] = 'make install'
if WITH_SYSTEM_NCCL:
my_env["NCCL_ROOT_DIR"] = NCCL_ROOT_DIR
if WITH_CUDA:
my_env["CUDA_BIN_PATH"] = CUDA_HOME
build_libs_cmd += ['--with-cuda']
if WITH_NNPACK:
build_libs_cmd += ['--with-nnpack']
if WITH_CUDNN:
my_env["CUDNN_LIB_DIR"] = CUDNN_LIB_DIR
my_env["CUDNN_INCLUDE_DIR"] = CUDNN_INCLUDE_DIR
if subprocess.call(build_libs_cmd + libs, env=my_env) != 0:
sys.exit(1)
if 'ATen' in libs:
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
generate_nn_wrappers()
def generate_code(ninja_global=None,
declarations_path=None,
nn_path=None,
install_dir=None):
# if ninja is enabled, we just register this file as something
# ninja will need to call if needed
if ninja_global is not None:
return generate_code_ninja(ninja_global)
# cwrap depends on pyyaml, so we can't import it earlier
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.insert(0, root)
from tools.autograd.gen_autograd import gen_autograd
from tools.jit.gen_jit_dispatch import gen_jit_dispatch
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
# Build THNN/THCUNN.cwrap and then THNN/THCUNN.cpp. These are primarily
# used by the legacy NN bindings.
generate_nn_wrappers(nn_path, install_dir, 'tools/cwrap/plugins/templates')
# Build ATen based Variable classes
autograd_gen_dir = install_dir or 'torch/csrc/autograd/generated'
jit_gen_dir = install_dir or 'torch/csrc/jit/generated'
for d in (autograd_gen_dir, jit_gen_dir):
if not os.path.exists(d):
os.makedirs(d)
gen_autograd(declarations_path or DECLARATIONS_PATH, autograd_gen_dir, 'tools/autograd')
gen_jit_dispatch(declarations_path or DECLARATIONS_PATH, jit_gen_dir, 'tools/jit/templates')
def generate_code(ninja_global=None, declarations_path=None, nn_path=None):
# if ninja is enabled, we just register this file as something
# ninja will need to call if needed
if ninja_global is not None:
return generate_code_ninja(ninja_global)
# cwrap depends on pyyaml, so we can't import it earlier
root = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.insert(0, root)
from tools.autograd.gen_autograd import gen_autograd
from tools.jit.gen_jit_dispatch import gen_jit_dispatch
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
# Build THNN/THCUNN.cwrap and then THNN/THCUNN.cpp. These are primarily
# used by the legacy NN bindings.
generate_nn_wrappers(nn_path)
# Build ATen based Variable classes
autograd_gen_dir = 'torch/csrc/autograd/generated'
jit_gen_dir = 'torch/csrc/jit/generated'
for d in (autograd_gen_dir, jit_gen_dir):
if not os.path.exists(d):
os.mkdir(d)
gen_autograd(declarations_path or DECLARATIONS_PATH, autograd_gen_dir)
gen_jit_dispatch(declarations_path or DECLARATIONS_PATH, jit_gen_dir)
def generate_code(ninja_global=None):
# if ninja is enabled, we just register this file as something
# ninja will need to call if needed
if ninja_global is not None:
return generate_code_ninja(ninja_global)
# cwrap depends on pyyaml, so we can't import it earlier
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.insert(0, root)
from tools.autograd.gen_autograd import gen_autograd
from tools.jit.gen_jit_dispatch import gen_jit_dispatch
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
# Build THNN/THCUNN.cwrap and then THNN/THCUNN.cpp. These are primarily
# used by the legacy NN bindings.
generate_nn_wrappers()
# Build ATen based Variable classes
autograd_gen_dir = 'torch/csrc/autograd/generated'
jit_gen_dir = 'torch/csrc/jit/generated'
for d in (autograd_gen_dir, jit_gen_dir):
if not os.path.exists(d):
os.mkdir(d)
gen_autograd(
'torch/lib/tmp_install/share/ATen/Declarations.yaml',
autograd_gen_dir)
gen_jit_dispatch(
'torch/lib/tmp_install/share/ATen/Declarations.yaml',
jit_gen_dir)
def run(self):
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
build_all_cmd = ['bash', 'torch/lib/build_all.sh']
if WITH_CUDA:
build_all_cmd += ['--with-cuda']
if subprocess.call(build_all_cmd) != 0:
sys.exit(1)
generate_nn_wrappers()
def run(self):
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
build_all_cmd = ['bash', 'torch/lib/build_all.sh']
if WITH_CUDA:
build_all_cmd += ['--with-cuda']
if WITH_NCCL and not SYSTEM_NCCL:
build_all_cmd += ['--with-nccl']
if WITH_DISTRIBUTED:
build_all_cmd += ['--with-distributed']
if subprocess.call(build_all_cmd) != 0:
sys.exit(1)
generate_nn_wrappers()
def run(self):
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
build_all_cmd = ['bash', 'torch/lib/build_all.sh']
if WITH_CUDA:
build_all_cmd += ['--with-cuda']
if WITH_NCCL and not SYSTEM_NCCL:
build_all_cmd += ['--with-nccl']
if WITH_DISTRIBUTED:
build_all_cmd += ['--with-distributed']
if subprocess.call(build_all_cmd) != 0:
sys.exit(1)
generate_nn_wrappers()
def run(self):
libs = ['TH', 'THS', 'THNN']
if WITH_CUDA:
libs += ['THC', 'THCS', 'THCUNN']
if WITH_NCCL and not SYSTEM_NCCL:
libs += ['nccl']
libs += ['THPP', 'libshm', 'ATen', 'nanopb']
if WITH_DISTRIBUTED:
if sys.platform.startswith('linux'):
libs += ['gloo']
libs += ['THD']
build_libs(libs)
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
generate_nn_wrappers()
def build_libs(libs):
for lib in libs:
assert lib in dep_libs, 'invalid lib: {}'.format(lib)
build_libs_cmd = ['bash', 'torch/lib/build_libs.sh']
my_env = os.environ.copy()
my_env["PYTORCH_PYTHON"] = sys.executable
if WITH_SYSTEM_NCCL:
my_env["NCCL_ROOT_DIR"] = NCCL_ROOT_DIR
if WITH_CUDA:
my_env["CUDA_BIN_PATH"] = CUDA_HOME
build_libs_cmd += ['--with-cuda']
if subprocess.call(build_libs_cmd + libs, env=my_env) != 0:
sys.exit(1)
if 'THNN' in libs or 'THCUNN' in libs:
from tools.nnwrap import generate_wrappers as generate_nn_wrappers
generate_nn_wrappers()
