U ‰d¹ ã@sfddlZddlmZmZeejejdœdd„Zejeejddœdd„Zejeeed œd d „ZdS) éN)ÚIterableÚOptional)Ú parametersÚreturncCs6d}g}|D]}t||ƒ}| | d¡¡q t |¡S)zâConvert parameters to one vector Args: parameters (Iterable[Tensor]): an iterator of Tensors that are the parameters of a model. Returns: The parameters represented by a single vector Néÿÿÿÿ)Ú_check_param_deviceÚappendÚviewÚtorchÚcat)rÚ param_deviceÚvecÚparam©rúE/tmp/pip-unpacked-wheel-ua33x9lu/torch/nn/utils/convert_parameters.pyÚparameters_to_vectors  r)r rrcCsjt|tjƒs td t |¡¡ƒ‚d}d}|D]8}t||ƒ}| ¡}||||… |¡j |_ ||7}q,dS)zîConvert one vector to the parameters Args: vec (Tensor): a single vector represents the parameters of a model. parameters (Iterable[Tensor]): an iterator of Tensors that are the parameters of a model. z"expected torch.Tensor, but got: {}Nr) Ú isinstancer ÚTensorÚ TypeErrorÚformatÚtypenamerZnumelZview_asÚdata)r rr ÚpointerrZ num_paramrrrÚvector_to_parameterss ÿ r)rÚold_param_devicercCsL|dkr|jr| ¡nd}n,d}|jr4| ¡|k}n|dk}|rHtdƒ‚|S)a'This helper function is to check if the parameters are located in the same device. Currently, the conversion between model parameters and single vector form is not supported for multiple allocations, e.g. parameters in different GPUs, or mixture of CPU/GPU. Args: param ([Tensor]): a Tensor of a parameter of a model old_param_device (int): the device where the first parameter of a model is allocated. Returns: old_param_device (int): report device for the first time NrFzKFound two parameters on different devices, this is currently not supported.)Zis_cudaZ get_devicer)rrÚwarnrrrr9sr) r ÚtypingrrrrrÚintrrrrrÚs