ó [T–hq ãób•%Sq\\S'Sq\\S'S\SS4SjrS\4SjrS\SS4SjrS\4S jrg) FÚ&_overwrite_module_params_on_conversionÚ!_swap_module_params_on_conversionÚvalueÚreturnNcó•Uqg)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. N©r©rs ÚH/var/www/auris/envauris/lib/python3.13/site-packages/torch/__future__.pyÚ)set_overwrite_module_params_on_conversionr s €ð".3Ñ*ócó•[$)a Returns whether to assign new tensors to the parameters instead of changing the existing parameters in-place when converting an :class:`torch.nn.Module`. Defaults to ``False``. See :func:`~torch.__future__.set_overwrite_module_params_on_conversion` for more information. r©r r Ú)get_overwrite_module_params_on_conversionrs €ô 2Ð1r có•Uqg)aù Sets whether to use :func:`~torch.utils.swap_tensors` instead of setting ``.data`` to change the existing parameters in-place when converting an ``nn.Module`` and instead of ``param.copy_(state_dict[key])`` when loading a state dict into an ``nn.Module``. .. note:: This function takes precedence over :func:`~torch.__future__.get_overwrite_module_params_on_conversion` When enabled, the following methods will swap the existing parameters in-place: #. ``module.{device}()`` (e.g. :meth:`nn.Module.cuda()`) for moving a module between devices #. ``module.{dtype}()`` (e.g. :meth:`nn.Module.float()`) for converting a module to a different dtype #. :meth:`nn.Module.to` #. :meth:`nn.Module.to_empty` #. :meth:`nn.Module.load_state_dict` The semantics for :meth:`~nn.Module.load_state_dict` when this is set are as follows: #. For each parameter/buffer, its corresponding ``state_dict['key']`` is transformed via :meth:`~torch.Tensor.module_load` (i.e. ``res = param.module_load(state_dict['key'])``) #. If necessary, ``res`` will be wrapped in an :class:`~nn.Parameter` #. The parameter/buffer in the module will be swapped via :func:`~torch.utils.swap_tensors` with ``res`` Args: value (bool): Whether to use :func:`~torch.utils.swap_tensors` or not. N©rrs r Ú$set_swap_module_params_on_conversionr#s €ð<).Ñ%r có•[$)a Returns whether to use :func:`~torch.utils.swap_tensors` instead of setting .data to change the existing parameters in-place when converting an ``nn.Module``. Defaults to ``False``. See :func:`~torch.__future__.set_swap_module_params_on_conversion` for more information. rr r r Ú$get_swap_module_params_on_conversionrDs €ô -Ð,r )rÚboolÚ__annotations__rr rrrr r r Úrs\ðØ4¨uÐ&¨Ó4Ø*/Ð! 4Ó/ð3°Tð3¸dô3ð(2°4ô2ð.°ð.¸ô.ðB-¨dõ-r