def __init__(self, dtype, shape):
self.host_accessor = None
if impl.current_cfg().ndarray_use_torch:
assert has_pytorch(
), "PyTorch must be available if you want to create a Taichi ndarray with PyTorch as its underlying storage."
# pylint: disable=E1101
self.arr = torch.zeros(shape,
dtype=to_pytorch_type(cook_dtype(dtype)))
if impl.current_cfg().arch == _ti_core.Arch.cuda:
self.arr = self.arr.cuda()
else:
self.arr = _ti_core.Ndarray(impl.get_runtime().prog,
cook_dtype(dtype), shape)
def __init__(self, dtype, arr_shape):
self.host_accessor = None
self.dtype = cook_dtype(dtype)
self.arr = _ti_core.Ndarray(impl.get_runtime().prog, cook_dtype(dtype),
arr_shape)