o h*@sddlZddlZddlmZmZmZmZmZmZddl m Z dddddZ ddd Z dd d Z dd d ZdddddZdddddZdS)N)_flatten_dense_tensors_get_device_index_handle_complex_reorder_tensors_as _take_tensors_unflatten_dense_tensors)nccl)outcCs^t|}|du|duAstd|d||dur(dd|D}tj||Stj||S)aBroadcasts a tensor to specified GPU devices. Args: tensor (Tensor): tensor to broadcast. Can be on CPU or GPU. devices (Iterable[torch.device, str or int], optional): an iterable of GPU devices, among which to broadcast. out (Sequence[Tensor], optional, keyword-only): the GPU tensors to store output results. .. note:: Exactly one of :attr:`devices` and :attr:`out` must be specified. Returns: - If :attr:`devices` is specified, a tuple containing copies of :attr:`tensor`, placed on :attr:`devices`. - If :attr:`out` is specified, a tuple containing :attr:`out` tensors, each containing a copy of :attr:`tensor`. NzFExactly one of 'devices' and 'out' must be specified, but got devices=z and out=cSg|]}t|qSr.0dr r j/var/www/html/construction_image-detection-poc/venv/lib/python3.10/site-packages/torch/nn/parallel/comm.py +zbroadcast..)r RuntimeErrortorch_C _broadcast_broadcast_out)tensordevicesr r r r broadcastsrcCs,dd|D}dd|D}tj|||S)a.Broadcast a sequence of tensors to the specified GPUs. Small tensors are first coalesced into a buffer to reduce the number of synchronizations. Args: tensors (sequence): tensors to broadcast. Must be on the same device, either CPU or GPU. devices (Iterable[torch.device, str or int]): an iterable of GPU devices, among which to broadcast. buffer_size (int): maximum size of the buffer used for coalescing Returns: A tuple containing copies of :attr:`tensor`, placed on :attr:`devices`. cSr r r r r r rr@rz'broadcast_coalesced..cSr r rrtr r rrAr)rr_broadcast_coalesced)tensorsr buffer_sizer r rbroadcast_coalesced1sr"c sbt|dd}|d}dt|D]?\}}|jjdks Jd||kr(|||krQddd |D}dd d |D}td |d |d |qdurZtdt |dkrd|dSt |rzt |}t j||d|St |jj|}fddt|D} || dj|dd}| ddD] } || j|ddq|S)aSum tensors from multiple GPUs. All inputs should have matching shapes, dtype, and layout. The output tensor will be of the same shape, dtype, and layout. Args: inputs (Iterable[Tensor]): an iterable of tensors to add. destination (int, optional): a device on which the output will be placed (default: current device). Returns: A tensor containing an elementwise sum of all inputs, placed on the :attr:`destination` device. T)optionalrNcpuz+reduce_add expects all inputs to be on GPUsxcs|]}t|VqdSNstrrr%r r r \zreduce_add..csr&r'r(r*r r rr+]r,zinput z has invalid size: got z, but expected zLreduce_add expects destination to be on the same GPU with one of the tensors)outputrootcsg|] \}}|kr|qSr r )rir root_indexr rrnszreduce_add..)device non_blocking)rsize enumerater3type get_devicejoin ValueErrorrlenr is_availabler empty_likereducetoadd_) inputs destination input_sizer0inpgotexpectedresultdestination_devicenonroototherr r1r reduce_addEs@       rKcsdd|D}g}g}t|D]<}tdd|Dr,t||}||||dqt||D]\}} || jr>| n| q1||ddqfdd|D} t| D]} dd| D} t| |} t| | dD]} || jqnqYtt ||S) a\Sum tensors from multiple GPUs. Small tensors are first coalesced into a buffer to reduce the number of synchronizations. Args: inputs (Iterable[Iterable[Tensor]]): iterable of iterables that contain tensors from a single device. destination (int, optional): a device on which the output will be placed (default: current device). buffer_size (int): maximum size of the buffer used for coalescing Returns: A tuple of tensors containing an elementwise sum of each group of inputs, placed on the ``destination`` device. cSsg|]}gqSr r )r_r r rrsz(reduce_add_coalesced..css|]}|jVqdSr') is_sparserr r rr+sz'reduce_add_coalesced..rcsg|]}t|qSr )r)rr r!r rrscSr r )r)rchunkr r rrs) zipallrKappendrMto_denserdatatupler)rArBr! dense_tensorsr. ref_ordertensor_at_gpusrGcollritrschunks flat_tensors flat_resultr rOrreduce_add_coalescedxs*     r_cCsxt|}|durdd|D}ttj|||||S|dur&td||dur1td|ttj||||S)a<Scatters tensor across multiple GPUs. Args: tensor (Tensor): tensor to scatter. Can be on CPU or GPU. devices (Iterable[torch.device, str or int], optional): an iterable of GPU devices, among which to scatter. chunk_sizes (Iterable[int], optional): sizes of chunks to be placed on each device. It should match :attr:`devices` in length and sums to ``tensor.size(dim)``. If not specified, :attr:`tensor` will be divided into equal chunks. dim (int, optional): A dimension along which to chunk :attr:`tensor`. Default: ``0``. streams (Iterable[torch.cuda.Stream], optional): an iterable of Streams, among which to execute the scatter. If not specified, the default stream will be utilized. out (Sequence[Tensor], optional, keyword-only): the GPU tensors to store output results. Sizes of these tensors must match that of :attr:`tensor`, except for :attr:`dim`, where the total size must sum to ``tensor.size(dim)``. .. note:: Exactly one of :attr:`devices` and :attr:`out` must be specified. When :attr:`out` is specified, :attr:`chunk_sizes` must not be specified and will be inferred from sizes of :attr:`out`. Returns: - If :attr:`devices` is specified, a tuple containing chunks of :attr:`tensor`, placed on :attr:`devices`. - If :attr:`out` is specified, a tuple containing :attr:`out` tensors, each containing a chunk of :attr:`tensor`. NcSr r r r r r rrrzscatter..zI'devices' must not be specified when 'out' is specified, but got devices=zQ'chunk_sizes' must not be specified when 'out' is specified, but got chunk_sizes=)rrVrr_scatterr _scatter_out)rr chunk_sizesdimstreamsr r r rscatters"recCsrdd|D}|dur&|dkrtjdtddt|ddd }tj|||S|dur1td |tj|||S) aGathers tensors from multiple GPU devices. Args: tensors (Iterable[Tensor]): an iterable of tensors to gather. Tensor sizes in all dimensions other than :attr:`dim` have to match. dim (int, optional): a dimension along which the tensors will be concatenated. Default: ``0``. destination (torch.device, str, or int, optional): the output device. Can be CPU or CUDA. Default: the current CUDA device. out (Tensor, optional, keyword-only): the tensor to store gather result. Its sizes must match those of :attr:`tensors`, except for :attr:`dim`, where the size must equal ``sum(tensor.size(dim) for tensor in tensors)``. Can be on CPU or CUDA. .. note:: :attr:`destination` must not be specified when :attr:`out` is specified. Returns: - If :attr:`destination` is specified, a tensor located on :attr:`destination` device, that is a result of concatenating :attr:`tensors` along :attr:`dim`. - If :attr:`out` is specified, the :attr:`out` tensor, now containing results of concatenating :attr:`tensors` along :attr:`dim`. cSr r rrr r rrrzgather..NrNzjUsing -1 to represent CPU tensor is deprecated. Please use a device object or string instead, e.g., "cpu".) stacklevelT) allow_cpur#zQ'destination' must not be specified when 'out' is specified, but got destination=) warningswarn FutureWarningrrr_gatherr _gather_out)r rcrBr r r rgathersrnr')r)Nr)NNrN)rN)rir torch._utilsrrrrrr torch.cudarrr"rKr_rernr r r rs   !  3/2