sg6 ddlmZmZmZmZddlZddlmcmcm Z ddl m Z ddl mZddlmZddlmZmZmZmZmZde ded eed eed ffd Zde ded eed eeed feed fffd Zdej4ded eed eeeeeffdZdej8j:deed efdZde ded eed eed ffdZ d ejBfdZ"y))castListSequenceTupleN) ShapeType) DeviceMesh) DTensorSpec) _StridedShardPartial Placement ReplicateShard global_shapemesh placementsreturn.cv|j}|yt|}t|}t|D]x\}}|j |}t |t s(|j} | |ks Jd| d||j|| |||\} } t | tsJ| || <zt|S)zl Compute the shape of a local shard of the given DTensor on its current coordinate of the mesh. )r Sharding dim  greater than tensor ndim ) get_coordinatelistlen enumeratesize isinstancerdim_local_shard_size_on_diminttuple) rrr my_coordinate local_shapendimidx placement mesh_dim_size shard_dimlocal_shard_size_s R/var/www/html/venv/lib/python3.12/site-packages/torch/distributed/tensor/_utils.pycompute_local_shaper*s'')M<( < ' 3 :NC IIcNM)U+%MM $O"9+-GvNO$&/&H&H *M=;M'# !""2C888)9 I& :[!!ch|j}|yt|}dgt|z}tt|Dcgc]}dg|jz}}dgt|z}t |D]\} } |j | } t| ts(| j} dgt|z} | t|ksJd| dt|| j|| | || d\}}||| <|| | <|| | | kr | | || <n|| xx| | z cc<|| xx| zcc<td|D}|r7d gt|z}d gt|z}t |D]\} } |j | } t| ts(| j} || rtd | d | d |d || rd|| <t| tr!d|| <|| | j| zz|| | <|| xx| zcc<|| || | <t |D cgc]0\} }tt!||Dcgc] \}}||z c}}2}}}} }t!||Dcgc] \}}||z }}}t#|t#|fScc}wcc}}wcc}}}} wcc}}w)a Compute the local tensor shape and the global offsets into the original tensor of a DTensor on its current global rank. This is useful for checkpointing purpose. Example (2 host with 4GPUs each): # Below is a DeviceMesh with mesh_shape of (2, 4) mesh = DeviceMesh(device_type="cuda", mesh=[ [0, 1, 2, 3], [4, 5, 6, 7] ], ) Let's say we distribute a global_tensor of shape (8,4) over the above DeviceMesh with a placements of [Shard(0), Shard(0)]. The local shape and global offset will be as follows: rank0 -- local_shape:[1, 4], global_offset:[0, 0] rank1 -- local_shape:[1, 4], global_offset:[1, 0] rank2 -- local_shape:[1, 4], global_offset:[2, 0] rank5 -- local_shape:[1, 4], global_offset:[5, 0] rank3 -- local_shape:[1, 4], global_offset:[3, 0] rank4 -- local_shape:[1, 4], global_offset:[4, 0] rank6 -- local_shape:[1, 4], global_offset:[6, 0] rank7 -- local_shape:[1, 4], global_offset:[7, 0] Let's say we distribute a global_tensor of shape (2) over the above DeviceMesh with a placements of [Shard(0)]. We will not have non-empty local tensor for all the ranks. The local shape and global offset will be as follows: rank0 -- local_shape:[1,], global_offset:[0,] rank1 -- local_shape:[1,], global_offset:[1,] rank2 -- local_shape:[0,], global_offset:[2,] rank5 -- local_shape:[0,], global_offset:[2,] rank3 -- local_shape:[0,], global_offset:[2,] rank4 -- local_shape:[0,], global_offset:[2,] rank6 -- local_shape:[0,], global_offset:[2,] rank7 -- local_shape:[0,], global_offset:[2,] )r-rrrT) return_offsetc3<K|]}t|tywN)rr ).0ps r) z8compute_local_shape_and_global_offset..sPz!];PsFzTStrided sharding does not allow Shard() to appear after the strided part has ended. z at idx z in z violates this assumption.)rrrranger"rrrrrranyNotImplementedErrorr split_factorsumzipr)rrrr r! global_offsetr(shard_idx_stride_by_mesh_dimnum_shards_by_tensor_dimr#r$r%r& local_offset shard_size shard_offsetstrided_shardingstrided_part_seenstrided_part_endshard_idx_stridexy shard_idxs r)%compute_local_shape_and_global_offsetrH1sdP'')M<( c,// %*3|+<%=( !QC$))O( $( %&3\):#: ' 3 ENC IIcNM)U+%MM !sS%66  3$["9+-GKHXGYZ[,5+M+M *!!#&"& ,N,( L*4 I&*6 Y' !+|I/FF/;I/FM),!), Y0GG,(3}D37 EhPZPP !&#l*; ;  %w\):: "+J"7 @Y $ # i/ ) I' 21;;D+XcURV)l*DF )36:(3!)];7;))45Y?%22]B5Y? 1; M;5Y?5Y?1 @<4=04/I/s+;]'KLtq!QULMI03; /JKtq!QUKMK[!5#777E( tMLs$J*J& J  J& 3J. J& tensorc t|j}t|j}t|D]\}}|j|}|j rt t |}|jdkrtd||j} | |jksJd| d|jd|d|| } | |z|| <tt|D]} | | k7s || || k\s|| |z|| <!t|ttfrtdt!|d||fS) aV Compute the global size and stride of a DTensor from the given local tensor. The local size is multiplited by `world_size` per Sharding dim. The local stride is multiplited by `world_size` per Sharding dim, as long as the dimension is outside sharding dim. For example, if we have a local tensor with size (4, 8, 2) and stride (16, 1, 8). If the DTensor placements are [Shard(2)] and world_size is 2; then the global size is (4, 8, 4) and stride is (16 * 2, 1, 8). Args: tensor (:class:`torch.Tensor`): Local tensor which DTensor will be constructed from. mesh (:class:`DeviceMesh`): Object which describes the mesh topology of devices for the DTensor. placements (Sequence[:class:`Placement`]]): The attribute of the DTensor that describes its layout on the mesh topology. Return: tensor_shape: A List of int which specifies the size of DTensor which build on top of the local tensor. tensor_stride: A List of int which specifies the stride of DTensor. rzOShard placements should have negative dims normalized in the user-facing APIs: rrz for placement number .zplacement type z not supported!)rrstrideris_shardrrrAssertionErrorr"r5rrr r RuntimeErrortype) rIrr tensor_shape tensor_strider#r$r%shard_placementr&local_dim_sizeis r)compute_global_tensor_inforVst8 &L)M#J/SY #    "5)4O""Q&$--<,=?(++IFKK' nyk)CFKK=Pfgjfkklm n'*)4N&4}&DL #3}-. H >mA&6- :R&R'4Q'7-'GM!$ HI 7';<i0AQR R3S4  &&r+op_callargsc>|D]}t|tjtfr|jcSt|t t fsHt|dkDsWt|dtjtfs{|djcStd|d)z Find the device mesh object from args. It returns None if no mesh is found. NOTE: we can optimize this search if needed rz+Cannot find device mesh from args for op : rK) rdtensorDTensorr device_meshrrr ValueError)rWrXargs r)try_find_mesh_from_argsr_s& cGOO[9 :?? " sT5M *C1 3q6GOO[#ABq6%% %& B7)1M NNr+ global_stridecpdgtzt|D]q\}}|jstt|j }t tD]*}||kDs|xx|j|zcc<,stfdt tDS)z Compute the stride of a local tensor shard, given the global stride of the DTensor. NOTE: Currently this function is assuming the DTensor is evenly shardable. r.c34K|]}||zywr1r-)r2rUr`stride_divisorss r)r4z'compute_local_stride..'s%34 aOA..s) rrrMrrrr5rr)r`rrmesh_idxr3rUjrcs` @r)compute_local_striderfscC ..O ,> ! ::<UA""A3}-. > #mA&66#A&$))H*==& > > 8=c->P8Q r+ct|tjr|St|tr|g}n;t |dk(r"t|dt rt |d}n t |}tj|S)z Unify variable types of size argument to torch.Size Acceptable types include: int, Sequence[int], Tuple[int], Tuple[Sequence[int]], or torch.Size r.r)rtorchSizerrrr)r torch_sizes r)normalize_to_torch_sizerk,se$ # $V TaJtAw9$q'] $Z ::j !!r+)#typingrrrrrhtorch.distributed.tensor._api distributedrI_apirZtorch._prims_commonrtorch.distributed.device_meshr&torch.distributed.tensor._dtensor_specr (torch.distributed.tensor.placement_typesr r r r rrr*rHTensorrV_ops OpOverloadobjectr_rfrirkr-r+r)rxsV.. //)4>""#-";CI;N" 38_">R8R8#-R8;CI;NR8 5c?E#s(O +,R8j8' LL8' *8'8@8K8' 49d3i  8'vO ZZ " "O*26*:OO*$.