def draw(self, n: int = 1, out: Optional[torch.Tensor] = None,
dtype: torch.dtype = torch.float32) -> torch.Tensor:
r"""
Function to draw a sequence of :attr:`n` points from a Sobol sequence.
Note that the samples are dependent on the previous samples. The size
of the result is :math:`(n, dimension)`.
Args:
n (Int, optional): The length of sequence of points to draw.
Default: 1
out (Tensor, optional): The output tensor
dtype (:class:`torch.dtype`, optional): the desired data type of the
returned tensor.
Default: ``torch.float32``
"""
if self.num_generated == 0:
if n == 1:
result = self._first_point.to(dtype)
else:
result, self.quasi = torch._sobol_engine_draw(
self.quasi, n - 1, self.sobolstate, self.dimension, self.num_generated, dtype=dtype,
)
result = torch.cat((self._first_point, result), dim=-2)
else:
result, self.quasi = torch._sobol_engine_draw(
self.quasi, n, self.sobolstate, self.dimension, self.num_generated - 1, dtype=dtype,
)
self.num_generated += n
if out is not None:
out.resize_as_(result).copy_(result)
return out
return result
def draw(self, n=1, out=None, dtype=torch.float32):
r"""
Function to draw a sequence of :attr:`n` points from a Sobol sequence.
Note that the samples are dependent on the previous samples. The size
of the result is :math:`(n, dimension)`.
Args:
n (Int, optional): The length of sequence of points to draw.
Default: 1
out (Tensor, optional): The output tensor
dtype (:class:`torch.dtype`, optional): the desired data type of the
returned tensor.
Default: ``torch.float32``
"""
result, self.quasi = torch._sobol_engine_draw(self.quasi,
n,
self.sobolstate,
self.dimension,
self.num_generated,
dtype=dtype)
self.num_generated += n
if out is not None:
out.resize_as_(result).copy_(result)
return out
return result