def _init_impl(path):
with dll_lock:
_IMPORTED_DYNDEPS.add(path)
with extension_loader.DlopenGuard():
ctypes.CDLL(path)
# reinitialize available ops
core.RefreshRegisteredOperators()
def InitOpsLibrary(name):
"""Loads a dynamic library that contains custom operators into Caffe2.
Since Caffe2 uses static variable registration, you can optionally load a
separate .so file that contains custom operators and registers that into
the caffe2 core binary. In C++, this is usually done by either declaring
dependency during compilation time, or via dynload. This allows us to do
registration similarly on the Python side.
Args:
name: a name that ends in .so, such as "my_custom_op.so". Otherwise,
the command will simply be ignored.
Returns:
None
"""
if not os.path.exists(name):
# Note(jiayq): if the name does not exist, instead of immediately
# failing we will simply print a warning, deferring failure to the
# time when an actual call is made.
print('Ignoring {} as it is not a valid file.'.format(name))
return
with extension_loader.DlopenGuard():
ctypes.CDLL(name)
# reinitialize available ops
core.RefreshRegisteredOperators()
def Python(self, f, grad_f=None):
with extension_loader.DlopenGuard():
import caffe2.python.op.python_ops_python as ops_python
RefreshRegisteredOperators()
assert (IsOperator('Python'))
token = ops_python.register(f)
if grad_f:
ops_python.register_gradient(token, grad_f)
return lambda *args, **kwargs: self._CreateAndAddToSelf(
'Python', token=token, *args, **kwargs)
def InitOpsLibrary(name):
"""Loads a dynamic library that contains custom operators into Caffe2.
Since Caffe2 uses static variable registration, you can optionally load a
separate .so file that contains custom operators and registers that into
the caffe2 core binary. In C++, this is usually done by either declaring
dependency during compilation time, or via dynload. This allows us to do
registration similarly on the Python side.
Args:
name: a name that ends in .so, such as "my_custom_op.so". Otherwise,
the command will simply be ignored.
Returns:
None
"""
if not name.endswith('.so'):
# TODO(jiayq): deal with extensions on platforms that do not use .so
# as extensions.
print('Ignoring {} as it is not an .so file.'.format(name))
return
with extension_loader.DlopenGuard():
ctypes.CDLL(name)
# reinitialize available ops
core.RefreshRegisteredOperators()
## @package _import_c_extension
# Module caffe2.python._import_c_extension
import atexit
import logging
import sys
from caffe2.python import extension_loader
# We will first try to load the gpu-enabled caffe2. If it fails, we will then
# attempt to load the cpu version. The cpu backend is the minimum required, so
# if that still fails, we will exit loud.
with extension_loader.DlopenGuard():
has_hip_support = False
has_cuda_support = False
has_gpu_support = False
try:
from caffe2.python.caffe2_pybind11_state_gpu import * # noqa
if num_cuda_devices(): # noqa
has_gpu_support = has_cuda_support = True
except ImportError as gpu_e:
logging.info('Failed to import cuda module: {}'.format(gpu_e))
try:
from caffe2.python.caffe2_pybind11_state_hip import * # noqa
# we stop checking whether we have AMD GPU devices on the host,
# because we may be constructing a net on a machine without GPU,
# and run the net on another one with GPU
has_gpu_support = has_hip_support = True
logging.info('This caffe2 python run has AMD GPU support!')
except ImportError as hip_e:
logging.info('Failed to import AMD hip module: {}'.format(hip_e))
## @package _import_c_extension
# Module caffe2.python._import_c_extension
import atexit
import logging
import sys
from caffe2.python import extension_loader
# We will first try to load the gpu-enabled caffe2. If it fails, we will then
# attempt to load the cpu version. The cpu backend is the minimum required, so
# if that still fails, we will exit loud.
with extension_loader.DlopenGuard():
has_hip_support = False
has_gpu_support = False
try:
from caffe2.python.caffe2_pybind11_state_gpu import * # noqa
if num_cuda_devices(): # noqa
has_gpu_support = True
except ImportError as gpu_e:
logging.info('Failed to import cuda module: {}'.format(gpu_e))
try:
RTLD_LAZY = 1
with extension_loader.DlopenGuard(RTLD_LAZY):
from caffe2.python.caffe2_pybind11_state_hip import * # noqa
if num_hip_devices():
has_hip_support = True
logging.info('This caffe2 python run has AMD GPU support!')
except ImportError as hip_e:
logging.info('Failed to import AMD hip module: {}'.format(hip_e))
logging.warning(
