
    9j6                     z   d dl Z d dlmZmZ d dlZd dlmZ d dlmc m	c m
Z d dlmc mZ d dlmZmZmZmZ d dlmZ d dlmZ d dlmZ d dlmZ d dlmZ d d	lmZ d d
lm Z m!Z!m"Z"mZ# d dl$m%Z%m&Z& dgZ'de!de(ejR                  ejR                  f   fdZ*de!de+de(ejR                  ejR                  f   fdZ,de!de(ejR                  ejR                  f   fdZ-de!de+defdZ.de!dej^                  defdZ0de!dej^                  fdZ1dejd                  dejf                  de+dejd                  fdZ4dejf                  de+de+de+dej^                  dejf                  fdZ5dejf                  de+d e de!fd!Z6dejf                  de(ejf                  e7e   f   fd"Z8de!d#e dz  dejf                  fd$Z9 G d% de      Z:y)&    N)Anycast)ShardShardedTensorShardedTensorMetadataTensorProperties)ShardMetadata)ChunkShardingSpec)_set_fsdp_flattened)FSDPExtensions)_create_chunk_sharded_tensor)_remote_device)
DeviceMeshDTensor	Replicater   )_flatten_tensor_unflatten_tensorDTensorExtensionstensorreturnc                    | j                   }|j                  dk7  rt        d      | j                  d   }dgt	        | j                               z  }|j                  d      }| j                  d   j                         r3t        t        |      j                  }| j                  |      |z  }|||<   t        j                  |      | j                  j                         fS )N   &Only 1D DeviceMeshes currently handledr   )mesh_dim)device_meshndimAssertionError
placementslensizeis_shardr   DSharddimtorchSize_local_tensor)r   r   	placementoffsets
num_chunks	shard_dim
chunk_sizes          f/media/conek/DATA/Code/OCR/venv/lib/python3.12/site-packages/torch/distributed/tensor/parallel/fsdp.py_get_boxr-      s    $$K1EFF!!!$IcC&&G!!1!-J $$&+//	[[+z9
'	JJw!5!5!:!:!<==    idxc                 x    t        |       \  }}t        j                  |D cg c]  }||z  	 c}      |fS c c}w N)r-   r$   r%   )r   r/   r(   r    vals        r,   _get_box_forr3   1   s6    V$MGTJJW5cc	56==5s   7c                 h    | j                   }|j                         }|t        t        | |d         S )Nr   )r   get_coordinater   r3   )r   r   coords      r,   _get_local_boxr7   6   s7    $$K&&(E}a))r.   dtcurrent_rankc                     | j                   }|j                  dk7  rt        d      t        |       \  }}t	        t        |      t        |      d| d| j                  j                         S )Nr   r   rank:/shard_offsetsshard_sizesr'   )r   r   r   r7   r	   listr&   device)r8   r9   meshr(   sizess        r,   _create_shard_md_from_dtrD   >   sh    >>DyyA~EFF#B'NGU7mK,q)9)9)@)@(AB r.   dt_pgc                    g }t        j                  |      }|dkD  rdnd}| j                  d   j                         r|j	                         }nd}t        |      D ]a  }t        | |      \  }}|j                  t        t        |      t        |      d|dkD  r|n| d| j                  j                                c t        || j	                         t        | j                  | j                  | j                               S )Nr   r   r;   r<   r=   )dtypelayoutrequires_grad)shards_metadatar    tensor_properties)distget_rankr   r!   r    ranger3   appendr	   r@   r&   rA   r   r   rG   rH   rI   )	r8   rE   	shards_mdmy_rankscapegoat_rankshard_countir(   rC   s	            r,   !_create_sharded_tensor_md_from_dtrU   K   s     ImmE"G!A+Q1N 
}}Q  "jjl; 

%b!,"7m Ka!eNA2CSCSCZCZB[\		


 !!WWY*((99**
	 	r.   c                 n    | j                   }|j                  dk7  rt        d      |j                         S )Nr   r   )r   r   r   	get_group)r8   rB   s     r,   
_get_dt_pgrX   s   s/    >>DyyA~EFF>>r.   specrankc                    t        | t              s| S d}| j                  D ]G  }t        t        |      }|j                         |k(  s'|j                         |j                  k7  sEd} n |rt        j                  |       } t        | j                        D ]o  \  }}t        t        |      }|j                         |k(  s*|j                         |j                  k7  sHt	        d| d|j                         | j                  |<   q | S )z
    Rewrite ``spec`` to match the device of ``tensor``.

    FSDP.sharded_optim_state_dict sneakly ships optimizer state to CPU so if the original ShardingSpec
    produces CUDA metadata, ST construction bombs.
    FTr;   r<   )

isinstancer
   r   r   r   rZ   rA   copydeepcopy	enumerate)rY   r   rZ   rewriteprT   r'   s          r,   _rewrite_spec_if_neededrb   z   s     d-. G__ #668t
fmm ;G	
 }}T"%doo6 	TLAy^Y7I~~4'I,<,<,>&--,O%3eD66==/4R%S"		T Kr.   
world_sizenum_devices_per_nodepgc           	         t        |       t        u rt        | j                               dk7  rt        | j                         }t        |||||      }| j                         d   }t        |t        j                  |j                              g}t        j                  | j                               }	d|	j                  _        t        j                  ||	| j                  d      }
|
S t        |       t        u r| j                   }|j"                  dk7  rt	        d      | j$                  }t        |||t&        j(                  j+                         |      }t-        |       }t        |t/        | t1        j2                  |                  g}t5        | |      }	d|	j                  _        t        j                  ||	|d      }
|
S t        | ||||      S )Nr   r   F)sharded_tensor_metadataprocess_group
init_rrefsr   )typer   r   local_shardsr   local_tensorr   r   r]   r^   metadatarK   rI   +_init_from_local_shards_and_global_metadata_process_groupr   r   r   r&   r$   acceleratordevice_countrX   rD   rL   rM   rU   )r   rZ   rc   rd   re   inner_paraminner_stouter_local_shardshardsst_metast_outerr   rE   s                r,   _chunk_tensorrx      s    F|}$v""$%*  ))+/ 
 #//1!4(DMM*;*D*DEF
 -- 1227!!/ LL$+ //	
 	f	 ((q  !IJJ**/**,
 6" (4VT]]5=QRS
 4FEB27!!/ LL$+	
 + 
 	
r.   r   c                    ||j                         nd}|t        d      |j                  dk  rt        d|j                   dd      | j                         j	                         } t        | t        j                        rt        | t              st        |j                        D cg c]  }t                }}t        |j                        D cg c]  }t                }}t        d      |d<   t        j                  | ||d	      j                  ||
      S | j                  }|d   }| j                         } t        |j                        D cg c]  }t                }}||d<   t        |j                        D 	cg c]  }	t                }}	t        d      |d<   ||d<   t        j                  | ||d	      j                  ||
      S c c}w c c}w c c}w c c}	w )z
    Shard a tensor to chunks along the first dimension.

    The local rank will gets its corresponding chunk as the local tensor to create a DTensor.
    Nz4No parent device_mesh is found for FSDP device_mesh.   z!Found parent device_mesh of ndim=,zbut meshes must be at least 2D.r   F)	run_checkr   r   )_get_root_meshRuntimeErrorr   detachcloner\   r$   Tensorr   rN   r   r"   
from_localredistributer   to_local)
r   rZ   r   	root_mesh_replicate_placementsshard_placementstp_placementstp_placementrT   s
             r,   _chunk_dtensorr      s    1<0G**,TIQRR~~/	/?qA-
 	
 ]]_""$F
 &%,,'
670K 6;9>>5JK	KK16y~~1FGAIKGG$Qi!!I3u

,!'  
	
 ))$Q'" 6;9>>5JK	KK#/R 16y~~1FGAIKGG%ay+!!I3u

,!'  
	
9  LG*  LGs   *GGG G%c                    t        t        |       j                         }t        |      dk(  r?t	        |d   j
                        t        u r!|d   j
                  }|j                         }|} | t        |      dkD  r|fS g fS )Nr   r   )r   r   rk   r   rj   r   )r   ru   inner_tensors      r,   _pre_load_state_dictr   &  sz     -(557F
6{aD!1!12mCay''**,c&kAoF66266r.   parent_meshc                 (   || j                   k7  rt        t        t        j                  | j
                              }t        t        |      dz
        D ]  }t               ||<    | j                  | j                   |      } | j                         S )zGAll gather a DTensor in its FSDP dimension and return the local tensor.r   r}   )r   r   r@   r]   r^   r   rN   r   r   r   r   )r   r   r   rT   s       r,   _all_gather_dtensorr   2  s    
 f(((dmmF$5$567J 3z?Q&' $!
1$  && ! F
 ??r.   c                       e Zd ZdZd fdZdej                  deej                  edz  f   fdZ	dej                  dedej                  fdZ
	 ddej                  d	ed
ededej                  dej                  dz  dej                  fdZdej                  d	ededej                  fdZdej                  deej                  ee   f   fdZdededz  dej                  fdZ xZS )r   z
    DTensorExtension is the TensorFlattener extension needed for 2D FSDP + TP.

    This is the implementation for FSDPExtensions defined in
    https://github.com/pytorch/pytorch/blob/main/torch/distributed/fsdp/_fsdp_extensions.py
    r   Nc                     t         |           d | _        || _        t        j
                  j                  | j                        | _        y r1   )super__init__compute_streamdevice_handler$   _dynamodisablepost_unflatten_transform)selfr   	__class__s     r,   r   zDTensorExtensions.__init__O  s@    "* ).(=(=)))
%r.   r   c                     t        |      S r1   )r   r   r   s     r,   pre_flatten_transformz'DTensorExtensions.pre_flatten_transformY  s     v&&r.   param_extensionc                    | j                   xs | j                  j                         }| j                  j                  |      5  t	        ||| j                  | j                         }t        |       |cd d d        S # 1 sw Y   y xY w)N)r   r   )r   r   current_streamstreamr   r   )r   r   r   r   results        r,   r   z*DTensorExtensions.post_unflatten_transform_  s}     $$K(:(:(I(I(K&&v. 	 '"00#22	F  '	 	 	s   0A>>BrZ   rc   rd   re   rA   c                      t        |||||      S r1   )rx   )r   r   rZ   rc   rd   re   rA   s          r,   chunk_tensorzDTensorExtensions.chunk_tensorr  s     VT:7KRPPr.   r   c                     t        |||      S r1   )r   )r   r   rZ   r   s       r,   chunk_dtensorzDTensorExtensions.chunk_dtensor}  s     fdK88r.   c                     t        |      S r1   )r   r   s     r,   pre_load_state_dict_transformz/DTensorExtensions.pre_load_state_dict_transform  s     $F++r.   r   c                     t        ||      S r1   )r   )r   r   r   s      r,   all_gather_dtensorz$DTensorExtensions.all_gather_dtensor  s    
 #6;77r.   )r   Nr1   )__name__
__module____qualname____doc__r   r$   r   tupler   r   r   intrL   ProcessGrouprA   r   r   r   r@   r   r   r   r   __classcell__)r   s   @r,   r   r   G  sV   
'' 
u||S4Z'	('ll58	4 '+	Q	Q 	Q 		Q
 "	Q 	Q t#	Q 
	Q99 9  	9
 
9,, 
u||T%[(	),88  $&8 
	8r.   );r]   typingr   r   r$   torch.distributeddistributedrL   &torch.distributed._shard.sharding_spec_shardsharding_spec
shard_spec"torch.distributed.distributed_c10ddistributed_c10dc10d'torch.distributed._shard.sharded_tensorr   r   r   r   r	   :torch.distributed._shard.sharding_spec.chunk_sharding_specr
   $torch.distributed.fsdp._common_utilsr   'torch.distributed.fsdp._fsdp_extensionsr   #torch.distributed.fsdp._shard_utilsr   torch.distributed.remote_devicer   torch.distributed.tensorr   r   r   r"   6torch.distributed.tensor.parallel._data_parallel_utilsr   r   __all__r   r%   r-   r   r3   r7   rD   r   rU   rX   ShardingSpecr   rb   rx   r   r@   r   r   r    r.   r,   <module>r      s5        ; ; 1 1  A X D B L : T T 
>W >uzz5::'=!> >$> >s >uUZZ5K/L >
*7 *uUZZ-C'D *
 
 
 
%%))%%P7 t00 

!
!+0<<?B>I
LLI

I
 I
 	I

 	I
 \\I
X>
LL>

>
 >
 	>
B	7LL	7
5<<e$%	7d" \\*I8 I8r.   