It is defined in __init__.py so that it exists even when `cuda_available`
is False (this is necessary to avoid breaking the test suite).
"""
def make_thunk(self, node, storage_map, compute_map, no_recycling):
if theano.sandbox.cuda.use.device_number is None:
theano.sandbox.cuda.use("gpu",
force=True,
default_to_move_computation_to_gpu=False,
move_shared_float32_to_gpu=False,
enable_cuda=False)
return super(GpuOp, self).make_thunk(node, storage_map, compute_map,
no_recycling)
theano.compile.debugmode.default_make_thunk.append(
get_unbound_function(GpuOp.make_thunk))
# We must do those import to be able to create the full doc when
# nvcc is not available
from theano.sandbox.cuda.var import (CudaNdarrayVariable, CudaNdarrayConstant,
CudaNdarraySharedVariable,
float32_shared_constructor)
from theano.sandbox.cuda.type import CudaNdarrayType
if cuda_available:
# check if their is an old cuda_ndarray that was loading instead of the one
# we compiled!
import cuda_ndarray.cuda_ndarray
if cuda_ndarray_so != cuda_ndarray.cuda_ndarray.__file__:
_logger.warning(
"cuda_ndarray was loaded from %s, but Theano expected "
is False (this is necessary to avoid breaking the test suite).
"""
def make_thunk(self, node, storage_map, compute_map, no_recycling):
if use.device_number is None:
use("gpu",
force=True,
default_to_move_computation_to_gpu=False,
move_shared_float32_to_gpu=False,
enable_cuda=False)
return super(GpuOp, self).make_thunk(node, storage_map,
compute_map, no_recycling)
theano.compile.debugmode.default_make_thunk.append(
get_unbound_function(GpuOp.make_thunk))
# We must do those import to be able to create the full doc when
# nvcc is not available
from theano.sandbox.cuda.var import (CudaNdarrayVariable,
CudaNdarrayConstant,
CudaNdarraySharedVariable,
float32_shared_constructor)
from theano.sandbox.cuda.type import CudaNdarrayType
def dnn_available():
if config.dnn.enabled == "False":
dnn_available.avail = False
dnn_available.msg = "Disabled by dnn.enabled flag"
if dnn_available.avail is None and not cuda_available:
def __hash__(self):
msg = []
msg.append(self.__class__.__name__)
for val in (self.partial_sum, self.pad, self.dense_connectivity,
self.stride, self.copy_non_contiguous):
msg.append(str(val))
return hash(tuple(msg))
# Make sure the cuda_convnet library is compiled and up-to-date
def make_thunk(self, *args, **kwargs):
if not convnet_available():
raise RuntimeError('Could not compile cuda_convnet')
return super(BaseActs, self).make_thunk(*args, **kwargs)
# This is needed as otherwise DebugMode will consider that
# BaseActs.make_thunk do something else then the default code, and
# would duplicate verification.
theano.compile.debugmode.default_make_thunk.append(
get_unbound_function(BaseActs.make_thunk))
class UnimplementedError(Exception):
"""
Like NotImplementedError, but designed not to be caught and suppressed
by theano.
"""
It is defined in __init__.py so that it exists even when `cuda_available`
is False (this is necessary to avoid breaking the test suite).
"""
def make_thunk(self, node, storage_map, compute_map, no_recycling):
if theano.sandbox.cuda.use.device_number is None:
theano.sandbox.cuda.use("gpu",
force=True,
default_to_move_computation_to_gpu=False,
move_shared_float32_to_gpu=False,
enable_cuda=False)
return super(GpuOp, self).make_thunk(node, storage_map,
compute_map, no_recycling)
theano.compile.debugmode.default_make_thunk.append(get_unbound_function(GpuOp.make_thunk))
# We must do those import to be able to create the full doc when
# nvcc is not available
from theano.sandbox.cuda.var import (CudaNdarrayVariable,
CudaNdarrayConstant,
CudaNdarraySharedVariable,
float32_shared_constructor)
from theano.sandbox.cuda.type import CudaNdarrayType
if cuda_available:
# check if their is an old cuda_ndarray that was loading instead of the one
# we compiled!
import cuda_ndarray.cuda_ndarray
if cuda_ndarray_so != cuda_ndarray.cuda_ndarray.__file__:
self.copy_non_contiguous == other.copy_non_contiguous)
def __hash__(self):
msg = []
msg.append(self.__class__.__name__)
for val in (self.partial_sum, self.pad, self.dense_connectivity,
self.stride, self.copy_non_contiguous):
msg.append(str(val))
return hash(tuple(msg))
# Make sure the cuda_convnet library is compiled and up-to-date
def make_thunk(self, *args, **kwargs):
if not convnet_available():
raise RuntimeError('Could not compile cuda_convnet')
return super(BaseActs, self).make_thunk(*args, **kwargs)
# This is needed as otherwise DebugMode will consider that
# BaseActs.make_thunk do something else then the default code, and
# would duplicate verification.
theano.compile.debugmode.default_make_thunk.append(
get_unbound_function(BaseActs.make_thunk))
class UnimplementedError(Exception):
"""
Like NotImplementedError, but designed not to be caught and suppressed
by theano.
"""