def decorator(func):
fused_func = cupy.fuse(func)
@functools.wraps(func)
def wrapper(self, fusion_mode):
if fusion_mode == 'enabled':
fused_func(*args)
elif fusion_mode == 'disabled':
func(*args)
elif fusion_mode == 'compile':
fused_func.clear_cache()
dtypes = [_.dtype for _ in args]
fused_func._compile_from_dtypes(*dtypes)
else:
raise ValueError('Invalid parameter')
uniform = cupy.random.uniform
args = []
if shape_args:
assert len(shapes_dict) == 0
for name in inspect.getargspec(func).args:
args.append(uniform(0, 200, shape_args, cupy.float32))
else:
for name in inspect.getargspec(func).args:
shape = shapes_dict[name]
args.append(uniform(0, 200, shape, cupy.float32))
# TODO (imanishi)
# fused_func.compile(*args)
fused_func(*args)
return wrapper
def fuse(*args, **kwargs):
"""Function fusing decorator.
It calls :func:`cupy.fuse` when CuPy is available to make fused function
and does nothing otherwise.
.. seealso::
:func:`cupy.fuse`
"""
if available:
return cupy.fuse(*args, **kwargs)
else:
return lambda f: f
def fuse(*args, **kwargs):
"""Function fusing decorator.
It calls :func:`cupy.fuse` when CuPy is available to make fused function
and does nothing otherwise.
.. seealso::
:func:`cupy.fuse`
"""
if available:
return cupy.fuse(*args, **kwargs)
else:
return lambda f: f
def _check(self, func, n, gen, args, error_types=None):
assert n == len(args), (n, args)
if error_types is None:
error_types = ()
f = cupy.fuse(func)
# Prepare input arrays
if not isinstance(gen, tuple):
gen = (gen,) * n
data0 = tuple([g(*a) for g, a in zip(gen, args)])
data1 = tuple([_.copy() for _ in data0])
# Invoke non-fused function
try:
ret0 = func(*data0) # Non-fused
err0 = None
except Exception as e:
if type(e) not in error_types:
raise
ret0 = None
err0 = e
# Invoke fused function
try:
ret1 = f(*data1) # Fused
err1 = None
except Exception as e:
if type(e) not in error_types:
raise
ret1 = None
err1 = e
self.assertEqual(err0 is None, err1 is None)
if err0 is not None:
# Error
self.assertEqual(type(err0), type(err1))
self.assertEqual(str(err0), str(err1))
arrs0 = None
arrs1 = None
else:
# Success
self.assertEqual(ret0 is None, ret1 is None)
if ret0 is None:
# Both return values are None
ret0 = ()
ret1 = ()
else:
# Return values must have the same type
self.assertEqual(type(ret0), type(ret1))
if not isinstance(ret0, tuple):
# Single arrays are returned
ret0 = (ret0,)
ret1 = (ret1,)
else:
# Tuples are returned
self.assertEqual(len(ret0), len(ret1))
# Concatenate return values and input arrays
arrs0 = ret0 + data0
arrs1 = ret1 + data1
# Test they have same values
for nf, f in zip(arrs0, arrs1):
numpy.testing.assert_array_almost_equal(nf.get(), f.get())
return err0 is not None, (arrs0, arrs1)
def res(xxx, name, xp, dtype):
f = getattr(cupy, name)
val = func(xxx, name, xp, dtype)
return cupy.fuse(f)(*val)
