def to_numpy(self, dtype=None):
if dtype is None:
dtype = to_numpy_type(self.dtype)
import numpy as np # pylint: disable=C0415
arr = np.zeros(shape=self.shape, dtype=dtype)
from taichi._kernels import tensor_to_ext_arr # pylint: disable=C0415
tensor_to_ext_arr(self, arr)
taichi.lang.runtime_ops.sync()
return arr
def to_torch(self, device=None):
import torch # pylint: disable=C0415
# pylint: disable=E1101
arr = torch.zeros(size=self.shape,
dtype=to_pytorch_type(self.dtype),
device=device)
from taichi._kernels import tensor_to_ext_arr # pylint: disable=C0415
tensor_to_ext_arr(self, arr)
taichi.lang.runtime_ops.sync()
return arr
def to_paddle(self, place=None):
"""Converts this field to a `paddle.Tensor`.
"""
import paddle # pylint: disable=C0415
# pylint: disable=E1101
# paddle.empty() doesn't support argument `place``
arr = paddle.to_tensor(paddle.zeros(self.shape,
to_paddle_type(self.dtype)),
place=place)
from taichi._kernels import tensor_to_ext_arr # pylint: disable=C0415
tensor_to_ext_arr(self, arr)
taichi.lang.runtime_ops.sync()
return arr
