3ia+ddlZddlZddlmZmZmZmZmZmZddl m Z d dddZ d dZ d dZ d dZdddd Zdddd Zy)N)_flatten_dense_tensors_get_device_index_handle_complex_reorder_tensors_as _take_tensors_unflatten_dense_tensors)nccl)outc t|}|du|duz std|d||8|Dcgc] }t|}}tjj ||Stjj ||Scc}w)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=)r RuntimeErrorrtorch_C _broadcast_broadcast_out)tensordevicesr ds X/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/torch/nn/parallel/comm.py broadcastrs*V $F _ -TU\T]]fgjfk l  189A$Q'99xx""6733xx&&vs33 :sBc|Dcgc] }t|}}|Dcgc] }t|}}tjj |||Scc}wcc}w)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`. )rrr r_broadcast_coalesced)tensorsr buffer_sizerts rbroadcast_coalescedr2sV.55 #5G5+23aq!3G3 88 ( ('; GG63s AAc t|d}|dj}d}t|D]\}}|jjdk(rt d|d|j |k(r|}|j|k7sWdjd |jD}djd |D}td |d |d || tdt|dk(r|dStj|r2tj||}tj||||Stj||jj|} t|D cgc] \}} ||k7s | } }} ||| dj!| dz}| ddD]$} |j#| j!| d&|Scc} }w)aSum tensors from multiple GPUs. All inputs should have matching shapes, dtype, and layout. The output tensor will be of the same shape, dtype, and layout. Args: inputs (Iterable[Tensor]): an iterable of tensors to add. destination (int, optional): a device on which the output will be placed (default: current device). Returns: A tensor containing an elementwise sum of all inputs, placed on the :attr:`destination` device. T)optionalrNcpuz7reduce_add expects all inputs to be on GPUs, but input z is on CPUxc32K|]}t|ywNstr.0rs r zreduce_add..`s6a3q66c32K|]}t|ywr!r"r$s rr&zreduce_add..as;1A;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)outputroot)device non_blocking)rsize enumerater,typeAssertionError get_devicejoin ValueErrorr lenr is_availabler empty_likereducetoadd_) inputs destination input_size root_indexiinpgotexpectedresultdestination_devicernonrootothers r reduce_addrGFs$K$?K!JJF# 3 ::??e # I!JW  >> { *J 88: #((6388:66Cxx; ;;H23%xjQ   Z   6{aay  !!&"45 F6 ; M#\\&*<*C*C*H*H+V!*6!2FAa:o1FF #gajmm%D'4'  QR[ PE KK(:N O P MGs : GGc|Dcgc]}g}}g}g}t|ddiD]}td|Dr2t||}|j||j|dGt||dD]2\} } | j| jr| j n| 4|j|dd|D cgc]} t | |} } t| ddiD]U} | Dcgc] }t|}}t||}t|| dD]} |j| jWtt||Scc}wcc} wcc}w)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. strictTc34K|]}|jywr!) is_sparse)r%rs rr&z'reduce_add_coalesced..s3qq{{3sr)rI) zipallrGappendrKto_denserrrdatatupler)r;r<r_ dense_tensorsr* ref_ordertensor_at_gpusrCcollrritrschunkschunk flat_tensors flat_results rreduce_add_coalescedr]|sy&.4 4 4M 4 FIv3d33 3N3 3 rtsU 444DH(3l,9^0GPT0Gf*7D*7rs