8iq \Udaeed<daeed<deddfdZdefdZdeddfdZdefd ZdS) F&_overwrite_module_params_on_conversion!_swap_module_params_on_conversionvaluereturnNc |adS)a> Sets whether to assign new tensors to the parameters instead of changing the existing parameters in-place when converting an ``nn.Module``. When enabled, the following methods will assign new parameters to the module: #. ``module.{device}()`` (e.g. :meth:`nn.Module.cuda()`) for moving a module between devices #. ``module.{dtype}()`` (e.g. :meth:`nn.Module.float()`) for converting a module to a different dtype #. :meth:`nn.Module.to` #. :meth:`nn.Module.to_empty` Args: value (bool): Whether to assign new tensors or not. Nrrs C/var/www/icac/venv/lib/python3.11/site-packages/torch/__future__.py)set_overwrite_module_params_on_conversionr s".3***ctS)a! Returns whether to assign new tensors to the parameters instead of changing the existing parameters in-place when converting an :class:`torch.nn.Module`. Defaults to ``False``. See :func:`~torch.__future__.set_overwrite_module_params_on_conversion` for more information. rr r )get_overwrite_module_params_on_conversionrs  21r c |adS)aI Sets whether to use :func:`~torch.utils.swap_tensors` instead of setting ``.data`` to change the existing parameters in-place when converting an ``nn.Module`` and instead of ``param.copy_(state_dict[key])`` when loading a state dict into an ``nn.Module``. .. note:: This function takes precedence over :func:`~torch.__future__.get_overwrite_module_params_on_conversion` When enabled, the following methods will swap the existing parameters in-place: #. ``module.{device}()`` (e.g. :meth:`nn.Module.cuda()`) for moving a module between devices #. ``module.{dtype}()`` (e.g. :meth:`nn.Module.float()`) for converting a module to a different dtype #. :meth:`nn.Module.to` #. :meth:`nn.Module.to_empty` #. :meth:`nn.Module.load_state_dict` The semantics for :meth:`~nn.Module.load_state_dict` when this is set are as follows: #. For each parameter/buffer, its corresponding ``state_dict['key']`` is transformed via :meth:`~torch.Tensor.module_load` (i.e. ``res = param.module_load(state_dict['key'])``) #. If necessary, ``res`` will be wrapped in an :class:`~nn.Parameter` #. The parameter/buffer in the module will be swapped via :func:`~torch.utils.swap_tensors` with ``res`` Args: value (bool): Whether to use :func:`~torch.utils.swap_tensors` or not. Nrrs r $set_swap_module_params_on_conversionr#s<).%%%r ctS)a! Returns whether to use :func:`~torch.utils.swap_tensors` instead of setting .data to change the existing parameters in-place when converting an ``nn.Module``. Defaults to ``False``. See :func:`~torch.__future__.set_swap_module_params_on_conversion` for more information. rr r r $get_swap_module_params_on_conversionrDs  -,r )rbool__annotations__rr rrrr r r rs4u&444*/!4///3T3d3333(242222......B-d------r