+
    &j$                     .   ^ RI t ^ RIHt ^ RIHt ^ RIHt ^ RIt^ RIHt ^ RI	H
t
HtHt ]],          t]]]R3,          ,          tR R	 ltR
 R ltR R ltR R ltRR R lltR R ltR R ltR R lt]! R]R7      RR R ll4       tR R R lltR# )!    NCallable)Any)
deprecated)Tensor)_broadcast_to_and_flattentree_flattentree_unflatten.c                `    V ^8  d   QhR\         \        R,          ,          R\         R\        /# )   flat_in_dimsN	flat_argsreturn)listint)formats   "m/Users/jameslopez/projects/CWCArchive/cwc-podcast/.venv/lib/python3.14/site-packages/torch/_vmap_internals.py__annotate__r      s/      sTz" 	    c                 8  a \        W4       UUu. uF  w  r#Vf   K  VP                  V4      NK  	  uppoS'       dP   \        ;QJ d    V3R lS 4       F  '       g   K   RM	  RM! V3R lS 4       4      '       d   \        RS R24      hS^ ,          # u uppi )Nc              3   :   <"   T F  qS^ ,          8g  x  K  	  R# 5i)r   N ).0sizebatch_sizess   & r   	<genexpr>/_validate_and_get_batch_size.<locals>.<genexpr>   s     Jkd;q>1ks   TFzTvmap: Expected all tensors to have the same size in the mapped dimension, got sizes z for the mapped dimension)zipr   any
ValueError)r   r   in_dimargr   s   &&  @r   _validate_and_get_batch_sizer#      s     |77KF 	7K
 ssJkJsssJkJJJ$$/=0IK
 	
 q>s
   BBc                `    V ^8  d   QhR\         \        \         R3,          ,          R\        /# )r   batched_outputs.r   )r   tupler   )r   s   "r   r   r   "   s(      &5+="= # r   c                 H    \        V \        4      '       d   \        V 4      # ^# )   )
isinstancer&   len)r%   s   &r   _num_outputsr+   "   s    /5))?##r   c                b    V ^8  d   QhR\         R\        R\        . \        3,          R\        /# )r   valuenum_elementserror_message_lambdar   )r   r   r   strr&   )r   s   "r   r   r   *   s9     	 			 #2s7+	 		r   c                     \        V \        4      '       g   V 3V,          # \        V 4      V8w  d   \        V! 4       4      hV # N)r)   r&   r*   r    )r-   r.   r/   s   &&&r   	_as_tupler3   *   s>    
 eU##x,&&
5z\!-/00Lr   c                v    V ^8  d   QhR\         R\        R\        R\        R\        \        \        3,          /# )r   in_dimsargs
vmap_levelfuncr   )	in_dims_tr&   r   r   )r   s   "r   r   r   8   sJ     9A 9A9A
9A 9A 	9A
 5#:9Ar   c                 F   \        V \        4      '       g>   \        V \        4      '       g(   \        R \	        V4       RV  R\        V 4       R24      h\        V4      ^ 8X  d   \        R \	        V4       R24      h\        V4      w  rE\        W4      pVf2   \        R \	        V4       RV  R\        V 4      ^,           RV R2	4      h\        WF4       F  w  rx\        V\        4      '       g#   Ve   \        R \	        V4       RV  RV R24      h\        V\        4      '       dA   \        V\        4      '       g+   \        R \	        V4       RV  RV R	\        V4       R
2	4      hVf   K  V^ 8  g   WP                  4       8  g   K  \        R \	        V4       RV  RV RVP                  4        RVP                  4        R24      h	  \        Wd4      p	\        Wd4       UUu. uF"  w  rVf   TM\        P                  ! WxV4      NK$  	  p
pp\        W4      V	3# u uppi )vmap(z
, in_dims=zv, ...)(<inputs>): expected `in_dims` to be int or a (potentially nested) tuple matching the structure of inputs, got: .z)(<inputs>): got no inputs. Maybe you forgot to add inputs, or you are trying to vmap over a function with no inputs. The latter is unsupported.zb, ...)(<inputs>): in_dims is not compatible with the structure of `inputs`. in_dims has structure z but inputs has structure z, ...)(<inputs>): Got in_dim=zE for an input but in_dim must be either an integer dimension or None.z' for an input but the input is of type zT. We cannot vmap over non-Tensor arguments, please use None as the respective in_dimz> for some input, but that input is a Tensor of dimensionality z- so expected in_dim to satisfy 0 <= in_dim < )r)   r   r&   r    	_get_nametyper*   r	   r   r   r   dimr#   torch_add_batch_dimr
   )r5   r6   r7   r8   r   	args_specr   r"   r!   
batch_sizebatched_inputss   &&&&       r   _create_batched_inputsrE   8   sc    gs##Jw,F,FIdO$Jwi 866:7m_AG
 	

 4yA~IdO$ %) *
 	
 (-I,W@LIdO$Jwi 8%%1'%:1%=$> ?&Kq*
 	
 93&#&&6+=	$(
7) <$X &01 
 fc"":c6+B+B	$(
7) <$X%L9+ ;<  6A:7791D	$(
7) <$X &%%(WWYK 0!!$1.  4, .lFJ |77KF ~5#7#7Z#PP7   .4j@@	s   %(Hc                    V ^8  d   QhR\         \        \         R3,          ,          R\        R\        R\        R\        R\
        R\        /# )	r   r%   .out_dimsr7   rC   r8   allow_none_pass_throughr   )r   r&   
out_dims_tr   r   bool)r   s   "r   r   r   u   s\     #
 #
eFCK00#
#
 #
 	#

 #
 "#
 #
r   c                   aaaaa \        V 4      o\        SSVVV3R  l4      p\        V \        4      '       d#   V^ ,          p\        P
                  ! V SSV4      # V'       dG   \        ;QJ d!    . VV3R l\        W4       4       F  NK  	  5# ! VV3R l\        W4       4       4      # \        ;QJ d!    . VV3R l\        W4       4       F  NK  	  5# ! VV3R l\        W4       4       4      # )c            
      F   < R \        S 4       RS RS R\        S 4       R2	# )r;   , ..., out_dims=z0): `out_dims` must have one dim per output (got z outputs) of r<   )r=   )r8   num_outputsrG   s   r   <lambda>!_unwrap_batched.<locals>.<lambda>   s4    %	$((8
 C((3}M)D/ARRSUr   c              3   f   <"   T F&  w  rVe   \         P                  ! VSSV4      MR x  K(  	  R # 5ir2   r@   _remove_batch_dimr   outout_dimrC   r7   s   &  r   r   "_unwrap_batched.<locals>.<genexpr>   s@      
 !H ? ''ZWM !Hs   .1c              3   Z   <"   T F   w  r\         P                  ! VSSV4      x  K"  	  R # 5ir2   rR   rT   s   &  r   r   rW      s.      
 G ##CZII Gs   (+)r+   r3   r)   r   r@   rS   r&   r   )	r%   rG   r7   rC   r8   rH   out_dims_as_tuplerV   rN   s	   &ffff&  @r   _unwrap_batchedrZ   u   s     /K!	U /6**#A&&&
JPWXXu 
 !$O G
u 	
u 
 !$O G
 
 	
 u 
 #O G
u 	
u 
 #O G
 
 	
r   c                4    V ^8  d   QhR\         R\        RR/# )r   outputsr8   r   N)r   r   )r   s   "r   r   r      s!     
 
s 
( 
t 
r   c                 |   \        V \        4      '       d   R # \        V \        4      '       g1   \        R\	        V4       R\	        V4       R\        V 4       R24      h\        V 4       FN  w  r#\        V\        4      '       d   K  \        R\	        V4       R\	        V4       R\        V4       RV R2	4      h	  R # )Nr;   z	, ...): `z%` must only return Tensors, got type z as the return.z for return r<   )r)   r   r&   r    r=   r>   	enumerate)r\   r8   idxoutputs   &&  r   _validate_outputsra      s    '6""gu%%IdO$Iio-> ?!!%g@
 	
 !)ff%%IdO$Iio-> ?!!%fl3%qB
 	
 *r   c                4    V ^8  d   QhR\         R\        RR/# )r   rG   r8   r   N)rI   r   )r   s   "r   r   r      s"     

 

* 

H 

QU 

r   c                    \        V \        4      '       d   R # \        V \        4      '       d;   \        ;QJ d    R V  4       F  '       d   K   RM	  RM! R V  4       4      '       g   \	        R\        V4       RV  R24      hR # )Nc              3   B   "   T F  p\        V\        4      x  K  	  R # 5ir2   )r)   r   )r   rV   s   & r   r   6_check_out_dims_is_int_or_int_tuple.<locals>.<genexpr>   s      208W
7C  s   FTr;   rM   zu): `out_dims` must be an int or a tuple of int representing where in the outputs the vmapped dimension should appear.)r)   r   r&   allr    r=   )rG   r8   s   &&r   #_check_out_dims_is_int_or_int_tuplerg      s~    (C  h&&cc 2082ccc 2082 / / IdO$$4XJ ?/ 0
 	
/r   c                $    V ^8  d   QhR\         /# )r   r8   r   )r   s   "r   r   r      s      H r   c                 T    \        V R 4      '       d   V P                  # \        V 4      # )__name__)hasattrrj   repr)r8   s   &r   r=   r=      s%    tZ  }}
 :r   z@Please use `torch.vmap` instead of `torch._vmap_internals.vmap`.)categoryc                H    V ^8  d   QhR\         R\        R\        R\         /# )r   r8   r5   rG   r   )r   r9   rI   )r   s   "r   r   r      s(     * *x *) *: *h *r   c                    \        WV4      # )z,
Please use torch.vmap instead of this API.
)_vmap)r8   r5   rG   s   &&&r   vmaprq      s     ))r   c          
      T    V ^8  d   QhR\         R\        R\        R\        R\         /# )r   r8   r5   rG   rH   r   )r   r9   rI   rJ   )r   s   "r   r   r      s:        
     "	 
  r   c                 R   a aaa \         P                  ! S 4      VV VV3R  l4       pV# )c            	      P  < \        SS4       \        P                  P                  4       p \	        SWS4      w  r#S! V!  pS'       g   \        VS4       \        VSVVSSR 7      \        P                  P                  4        #   \        P                  P                  4        i ; i))rH   )rg   r@   _C_vmapmode_increment_nestingrE   ra   rZ   _vmapmode_decrement_nesting)	r6   r7   rD   rC   r%   rH   r8   r5   rG   s	   *    r   wrapped_vmap.<locals>.wrapped   s    +Hd;XX99;
	3)?4*&N #N3O*!/48"(? HH002EHH002s   9B  B%)	functoolswraps)r8   r5   rG   rH   rx   s   ffff r   rp   rp      s'     __T3 3* Nr   )F)r   r   )r   r   F)rz   collections.abcr   typingr   typing_extensionsr   r@   r   torch.utils._pytreer   r	   r
   r   r&   r9   rI   r#   r+   r3   rE   rZ   ra   rg   r=   FutureWarningrq   rp   r   r   r   <module>r      s     $  (   W W %K	5c?"
"	9Az#
T
"

 F*	*   r   