sg*ddlZddlmZddlZddlmZmZmZmZm Z m Z ddl m Z d dddZ d dZd dZdd Zdddd Zdddd Zy)N)List)_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 I/var/www/html/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`. )rrrr_broadcast_coalesced)tensorsr buffer_sizerts rbroadcast_coalescedr2sV.55 #5G5+23aq!3G3 88 ( ('; GG63s AAc t|d}|dj}d}t|D]\}}|jjdk7sJd|j |k(r|}|j|k7sOdj d|jD}dj d |D}td |d |d || td t|dk(r|dStj|r2tj||}tj||||Stj||jj|} t|D cgc] \}} ||k7s | } }} ||| dj| dz}| ddD]$} |j!| j| d&|Scc} }w)aSum tensors from multiple GPUs. All inputs should have matching shapes, dtype, and layout. The output tensor will be of the same shape, dtype, and layout. Args: inputs (Iterable[Tensor]): an iterable of tensors to add. destination (int, optional): a device on which the output will be placed (default: current device). Returns: A tensor containing an elementwise sum of all inputs, placed on the :attr:`destination` device. T)optionalrNcpuz+reduce_add expects all inputs to be on GPUsxc32K|]}t|ywNstr.0r s r zreduce_add..]s6a3q66c32K|]}t|ywr"r#r%s rr'zreduce_add..^s;1A;r(zinput z has invalid size: got z, but expected zLreduce_add expects destination to be on the same GPU with one of the tensors)outputroot)device non_blocking)rsize enumerater-type get_devicejoin ValueErrorr lenr is_availabler empty_likereducetoadd_) inputs destination input_size root_indexiinpgotexpectedresultdestination_devicernonrootothers r reduce_addrGFs$K$?K!JJF# 3zz%'V)VV' >> { *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 2 GGc|Dcgc]}g}}g}g}t|D]}td|Dr2t||}|j||j|dGt||D]2\} } | j| jr| j n| 4|j|dd|D cgc]} t | |} } t| D]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. c34K|]}|jywr") is_sparse)r&rs rr'z'reduce_add_coalesced..s3qq{{3sr) zipallrGappendrJto_denserrr datatupler)r;r<r_ dense_tensorsr+ ref_ordertensor_at_gpusrCcollrritrschunkschunk flat_tensors flat_results rreduce_add_coalescedr\ysk&.4 4 4M 4 FIv,3 3N3 3 rtsX 444BH(0f,9^/GPT/Gd*7D*7rs