def normal(self, loc=0.0, scale=1.0, size=None, dtype=float):
"""Returns an array of normally distributed samples.
.. seealso::
:func:`cupy.random.normal` for full documentation,
:meth:`numpy.random.RandomState.normal`
"""
dtype = _check_and_get_dtype(dtype)
size = _get_size(size)
out = cupy.empty(size, dtype=dtype)
if dtype.type == numpy.float32:
curand.generateNormal(self._generator, out._fptr, out.size, loc,
scale)
else:
curand.generateNormalDouble(self._generator, out._fptr, out.size,
loc, scale)
return out
def normal(self, loc=0.0, scale=1.0, size=None, dtype=float):
"""Returns an array of normally distributed samples.
.. seealso::
:func:`cupy.random.normal` for full documentation,
:meth:`numpy.random.RandomState.normal`
"""
dtype = _check_and_get_dtype(dtype)
size = _get_size(size)
out = cupy.empty(size, dtype=dtype)
if dtype.type == numpy.float32:
curand.generateNormal(self._generator, out._fptr, out.size, loc,
scale)
else:
curand.generateNormalDouble(self._generator, out._fptr, out.size,
loc, scale)
return out
def test_invalid_argument_normal_float(self):
out = cupy.empty((1,), dtype=numpy.float32)
with self.assertRaises(ValueError):
curand.generateNormal(
self.generator, out.data.ptr, 1, 0.0, 1.0)
