
    qi5                     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k(  sJ 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
placementslensizeis_shardr   DSharddimtorchSize_local_tensor)r   r   	placementoffsets
num_chunks	shard_dim
chunk_sizes          l/home/ubuntu/crypto_trading_bot/.venv/lib/python3.12/site-packages/torch/distributed/tensor/parallel/fsdp.py_get_boxr,      s    $$Kq J"JJ !!!$IcC&&G!!1!-J$$&+//	[[+z9
'	JJw!5!5!:!:!<==    idxc                 x    t        |       \  }}t        j                  |D cg c]  }||z  	 c}      |fS c c}w N)r,   r#   r$   )r   r.   r'   r   vals        r+   _get_box_forr2   /   s6    V$MGTJJW5cc	56==5s   7c                 `    | j                   }|j                         }|J t        | |d         S )Nr   )r   get_coordinater2   )r   r   coords      r+   _get_local_boxr6   4   s8    $$K&&(Ea))r-   dtcurrent_rankc                     | j                   }|j                  dk(  sJ d       t        |       \  }}t        t	        |      t	        |      d| d| j
                  j                         S )Nr   r   rank:/shard_offsetsshard_sizesr&   )r   r   r6   r	   listr%   device)r7   r8   meshr'   sizess        r+   _create_shard_md_from_dtrC   ;   sg    >>D99>CCC>#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   ranger2   appendr	   r?   r%   r@   r   r   rF   rG   rH   )	r7   rD   	shards_mdmy_rankscapegoat_rankshard_countir'   rB   s	            r+   !_create_sharded_tensor_md_from_dtrT   G   s     ImmE"G!A+Q1N	}}Q  "jjl; 

%b!,"7m Ka!eNA2CSCSCZCZB[\		


 !!WWY*((99**
	 	r-   c                 f    | j                   }|j                  dk(  sJ d       |j                         S )Nr   r   )r   r   	get_group)r7   rA   s     r+   
_get_dt_pgrW   n   s.    >>D99>CCC>>>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   rY   r@   copydeepcopy	enumerate)rX   r   rY   rewriteprS   r&   s          r+   _rewrite_spec_if_neededra   t   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k(  sJ | 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k(  sJ d       | j"                  }t        |||t$        j&                  j)                         |      }t+        |       }t        |t-        | t/        j0                  |                  g}t3        | |      }	d|	j                  _        t        j                  ||	|d      }
|
S t        | ||||      S )Nr   r   F)sharded_tensor_metadataprocess_group
init_rrefsr   )typer   r   local_shardslocal_tensorr   r   r\   r]   metadatarJ   rH   +_init_from_local_shards_and_global_metadata_process_groupr   r   r   r%   r#   acceleratordevice_countrW   rC   rK   rL   rT   )r   rY   rb   rc   rd   inner_paraminner_stouter_local_shardshardsst_metast_outerr   rD   s                r+   _chunk_tensorrw      s    F|}$6&&()Q...))+/ 
 #//1!4(DMM*;*D*DEF
 -- 1227!!/ LL$+ //	
 	f	 ((1$N&NN$**/**,
 6" (4VT]]5=QRS
 4FEB27!!/ LL$+	
 + 
 	
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   rM   r   r!   
from_localredistributer   to_local)
r   rY   r   	root_mesh_replicate_placementsshard_placementstp_placementstp_placementrS   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   rj   r   ri   r   )r   rt   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                   k(  sJ 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   rM   r   r   r   r   )r   r   r   rS   s       r+   _all_gather_dtensorr   *  s    
 &,,,,,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 r0   )super__init__compute_streamdevice_handler#   _dynamodisablepost_unflatten_transform)selfr   	__class__s     r+   r   zDTensorExtensions.__init__F  s@    "* ).(=(=)))
%r-   r   c                     t        |      S r0   )r   r   r   s     r+   pre_flatten_transformz'DTensorExtensions.pre_flatten_transformP  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_transformV  s}     $$K(:(:(I(I(K&&v. 	 '"00#22	F  '	 	 	s   0A>>BrY   rb   rc   rd   r@   c                      t        |||||      S r0   )rw   )r   r   rY   rb   rc   rd   r@   s          r+   chunk_tensorzDTensorExtensions.chunk_tensori  s     VT:7KRPPr-   r   c                     t        |||      S r0   )r   )r   r   rY   r   s       r+   chunk_dtensorzDTensorExtensions.chunk_dtensort  s     fdK88r-   c                     t        |      S r0   )r   r   s     r+   pre_load_state_dict_transformz/DTensorExtensions.pre_load_state_dict_transform|  s     $F++r-   r   c                     t        ||      S r0   )r   )r   r   r   s      r+   all_gather_dtensorz$DTensorExtensions.all_gather_dtensor  s    
 #6;77r-   )r   Nr0   )__name__
__module____qualname____doc__r   r#   r   tupler   r   r   intrK   ProcessGroupr@   r   r   r   r?   r   r   r   r   __classcell__)r   s   @r+   r   r   >  sV   
'' 
u||S4Z'	('ll58	4 '+	Q	Q 	Q 		Q
 "	Q 	Q t#	Q 
	Q99 9  	9
 
9,, 
u||T%[(	),88  $&8 
	8r-   );r\   typingr   r   r#   torch.distributeddistributedrK   &torch.distributed._shard.sharding_spec_shardsharding_spec
shard_spec"torch.distributed.distributed_c10ddistributed_c10dc10d'torch.distributed._shard.sharded_tensorr   r   r   r   r	   :torch.distributed._shard.sharding_spec.chunk_sharding_specr
   $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$   r,   r   r2   r6   rC   r   rT   rW   ShardingSpecr   ra   rw   r   r?   r   r   r    r-   r+   <module>r      s5        ; ; 1 1  A X D B L : T T 
>W >uzz5::'=!> > > >s >uUZZ5K/L >
*7 *uUZZ-C'D *	 	 	 	$$))$$N7 t00 

!
!+0<<?B>G
LLG

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

 	G
 \\G
T>
LL>

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