
    `iհ                     j   U d dl Z d dlmZmZmZmZmZmZmZ ee	e
f         Zd dlZdee	         dee	         fdZdee	         dee	         dee	         fdZdee	         dedee	         fdZd	ee	         d
ee	         fdZd	ee	         fdZd	ee	         fdZdee	         dee	         fdZd	ee	         dee	         fdZd	ee	         dee	         defdZdee	         de	dee	         fdZdee	         fdZd	ee	         dee	         fdZddd	ee	         dee	         defdZd	ee	         deee	                  dedefd Zd	ee	         d!e	defd"Zd#e	d$e	fd%Zd&e	d'e	d(e	d)e	d*e	d+e	d,efd-Zd&e	d'e	d(e	d*e	d+e	d,efd.Z d/ee	         d0e	d1e	d2e	d3e	d4e	d5e	d6e	d7e	d8e	d9e	d:e	d;e	d<e	fd=Z!d/ee	         d>ee	         d*ee	         d?ee	         d+ee	         d,efd@Z"d/ee	         d>ee	         d*ee	         d?ee	         d+ee	         d,efdAZ#d/ee	         dBeee	                  dCeee
                  fdDZ$d	ee	         dEee	         fdFZ%d	ee	         dGee	         fdHZ&d	ee	         dIee	         fdJZ'dKee	         d!e	fdLZ(dKee	         fdMZ)dKee	         d!e	fdNZ*dKee	         dOee	         fdPZ+d	ee	         d!e	dQee	         fdRZ,	 	 	 ddTee	         dUee	         dVe	dWedXef
dYZ-dZ Z.d	ee	         d!e	d[ee	         d\ee	         d]e	f
d^Z/d_eee	                  fd`Z0d!e	daeee	                  fdbZ1dGee	         fdcZ2ddee	         deee	         dfe	dQe	fdgZ3d_eee	                  d!e	fdhZ4d_eee	                  d!e	fdiZ5d	ee	         d!e	dQe	fdjZ6dkee	         dlee	         fdmZ7d	ee	         fdnZ8d	ee	         doe	dpe	fdqZ9d/ee	         dTee	         dreee	                  fdsZ:d	ee	         dtee	         dEee	         duedvef
dwZ;dxee	         defdyZ<d/ee	         dzee	         dreee	                  d*ee	         d?ee	         d+ee	         d{e	fd|Z=d}ee	         d~ee	         dreee	                  d*ee	         d?ee	         d+ee	         d{e	fdZ>d/ee	         dTee	         dreee	                  d*ee	         d?ee	         d+ee	         d{e	fdZ?d/ee	         dTee	         dreee	                  d*ee	         d?ee	         d+ee	         d{e	fdZ@dee	         d/ee	         dTee	         deee	                  fdZA	 	 	 	 	 	 dd/ee	         dTee	         dreee	                  d*eee	                  d?eee	                  deee	                  d{e	d+eee	                  dee	         fdZBd/ee	         dTee	         dreee	                  d*ee	         d?ee	         d+ee	         dedee	         d{e	dee	         fdZCd/ee	         dTee	         dreee	                  d*ee	         d?ee	         d+ee	         dedee	         d{e	dededededee	         fdZDd/ee	         dTeee	                  dreee	                  deee	                  deee	                  dede
de
defdZEd/ee	         dTee	         dreee	                  d*ee	         d?ee	         d+ee	         d{e	fdZFdd!e	de	defdZGd/efdZHdKee	         fdZId\ededededef
dZJd[ed\ededededefdZKd[ed\ed]ededededefdZLd/ee	         dOee	         fdZMd	ee	         dee	         dee	         dee	         fdZNd/ee	         de	de	fdZOd/ee	         fdZPd/ee	         fdZQd	ee	         d!e	defdZR	 dd	ee	         d!ee	         dedee	         fdZSd	ee	         dEee	         dee	         fdZTd	ee	         dee	         fdZUdd	ee	         de	d!e	deVee	         ee	         f         fdZWd	ee	         dee	         dTeee	                  de	deVee	         ee	         f         f
dZXd/ee	         dee	         deVee	         ee	         ee	         f         fdZYd/ee	         dTeee	                  dreee	                  deee	                  deee	                  dedeVee	         ee	         ee	         f         fdZZd/ee	         dTeee	                  dreee	                  deee	                  deee	                  deVee	         ee	         ee	         ee	         f         fdZ[	 	 	 	 dd	ee	         dee	         dTeee	                  de	de	de
dee	         fdZ\	 ej]        j^        Z_i a`eaebe_f         ecd<   i ZdeaebeVe_e_f         f         ecd<   i Zeeaee_f         ecd<   defdZfdebdefdĄZgdebdedefdǄZh egde            egde            egde            egde            egdeH            egdeH            egde            egde            egdeJ            egdeK            egdeL            egde)            egde*            egde+            egde(            egde/            egde6            egde,            egde            egde            egde            egde            egde-            egde%            egde&            egde'            egde7            egde:            egde"            egde#            egde8            egde9            egde?            egde@            egdeE            egdeF            egdeA            egdeC            egdeD            egdeB            egdeO            egde4            egde5            egdeM            egdeN            egde            egde            egde            egde            egde            egde            egdeH            egdeH            egde;            egde$            egde            egd e            egde            egde            egdeS            egdeT            egdeU            egdeW            egdeX            egdeY            egd	eZ            egd
eZ            egdeZ            egde[            egde\            egde            egde            egde            ehdePeQ           dS (      N)AnyCallableDictListOptionalTupleUnionabc           	         t          |           }t          |          }t          ||          }g }t          |          D ]}|dz
  |z
  }|dz
  |z
  }|dz
  |z
  }	|dk    r| |         nd}
|	dk    r||	         nd}|
|k    r$|
dk    r|dk    rt          d|
 d| d|           |                    |
dk    r|n|
           |S )N   r   zThe size of tensor a z" must match the size of tensor b (z) at non-singleton dimension )lenmaxrangeAssertionErrorappend)r
   r   dimsAdimsBndimexpandedSizesioffsetdimAdimBsizeAsizeBs               n/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torch/jit/_shape_functions.py	broadcastr      s   FFEFFEueD!M4[[ = =Aqy6!qy6! AII$A AII$AE>>eqjjUaZZ xxxQVxxuvxx   	eqjjUUe<<<<    cc                 >    t          t          | |          |          S Nr   r
   r   r    s      r   broadcast_threer%   3   s    Yq!__a(((r   c                 "    t          | |          S r"   r#   r$   s      r   broadcast_one_threer'   7   s    Q??r   selfoutc                    t          |          dk    sJ t          |           dk    st          |           dk    sJ t          dt          |                     D ]}| |         dk    sJ g }t          dt          |           dz
            D ]}|                    | |                    |D ]}|                    |           |S )N         r   r   )r   r   r   )r(   r)   r   shapeelems        r   adaptive_avg_pool2dr0   ;   s    s88q====t99>>SYY!^^^+1c$ii    Aw!|||||E1c$ii!m$$  T!W  TLr   c                 >    g }| D ]}|                     |           |S r"   r   )r(   r)   r/   s      r   _copyr3   I   s0    C  

4Jr   c                      t          |           S r"   r3   r(   s    r   unaryr7   P   s    ;;r   c                 X   t          |           }t          |          }||k    rt          d| d| d          t          |          D ]R}||z
  |z   }| |         }|dk    r||         nd}||k    r*|dk    r$t          d                    |||                    St	          |           S )NzThe dims of tensor b (z6) must be less than or equal to the dims of tensor a (z) r   r   zZThe size of tensor a {} must match the size of tensor b ({}) at non-singleton dimension {})r   r   r   formatr3   )r
   r   r   r   r   r   r   r   s           r   broadcast_inplacer:   T   s    FFEFFEu}}kUkkbgkkk
 
 	
 e 	 	u}t#$ AII$AE>>eqjj 44:F5%4N4N   88Or   sizesc                    t          |          t          |           k    sJ t          |          }t          |           }|dk    rt          |          S g }t          |          D ]_}|dz
  |z
  }|dz
  |z
  }|dk    r| |         nd}||         }	|	dk    r
|dk    sJ |}	||	k    r
|dk    sJ |	}|                    |           `|S )Nr   r   )r   r3   r   r   )
r(   r;   r   
tensor_dimr)   r   r   dimsize
targetSizes
             r   expandrB   h   s    u::T""""u::DTJqyyU||C4[[  A1nv%1HHtCyy!1X
!8888J:19999D

4Jr   inp0c                 "    t          | |          S r"   )rB   )r(   r;   rC   s      r   expand_one_unusedrE   ~   s    $r   r.   numelreturnc                 V   d}d }t          t          |                     D ]H}| |         dk    r|t          d          |}"| |         dk    r|| |         z  }:t          d          ||k    s ||dk    r	||z  dk    st          d          t          |           }|||z  ||<   |S )Nr   r=   z"only one dimension can be inferredr   zinvalid shape dimensionszinvalid shape)r   r   r   r3   )r.   rF   newsize	infer_dimr?   r)   s         r   infer_size_implrK      s    G#ISZZ   = =:$$%IJJJII3Z1__uSz!GG !;<<<!gkkego6J6J_---
,,C')IJr   c                     d}| D ]}||z  }|S Nr    )r;   rF   r/   s      r   rF   rF      s&    E  Lr   c                 <    t          |t          |                     S r"   )rK   rF   )r(   r;   s     r   viewrP      s    5%++...r   F)implicitrQ   c                "    t          | |          S r"   )rP   )r(   r;   rQ   s      r   view_one_unusedrS      s    er   opt_dimskeep_dimdtc           	         g }|t          |          dk    r*t          t          t          |                               }n|}t          t          |                     D ]a}d}|D ]%}|t          |t          |                     k    rd}&|r|r|                    d           F|                    | |                    b|S )Nr   FTr   )r   listr   maybe_wrap_dimr   )	r(   rT   rU   rV   r)   dimsidxis_mean_dim
reduce_dims	            r   sum_mean_dimr^      s     C3x==A--uSYY//00SYY 	" 	"! 	# 	#JnZT;;;;" 	" 

1JJtCy!!!!Jr   r?   c                 0    t          | |g|d           }||fS r"   )r^   )r(   r?   rU   r)   s       r   max_dimr`      s     
tcUHd
3
3C8Or   xyc                     | |z  S r"   rN   )ra   rb   s     r   div_rtnrd      s    6Mr   	inputSize
kernelSizepad_lpad_rstridedilation	ceil_modec                     t          | |z   |z   ||dz
  z  z
  dz
  |r|dz
  ndz   |          dz   }|r|dz
  |z  | |z   k    r|dz
  }|S Nr   r   )rd   )re   rf   rg   rh   ri   rj   rk   
outputSizes           r   pooling_output_shape_pad_lrro      s     	 *q.)* 	
 '-vzzA/ 	
 	
 		   (Nf$	E(999#aJr   c           	      L    |dk    s
J d            t          | ||||||          S )Nr   zstride should not be zeero)ro   )re   rf   rg   ri   rj   rk   s         r   pooling_output_shaperq      s9     Q;;;4;;;&:ueVXy  r   inputkHkWdHdWpadHpadW	dilationH	dilationWnInputPlaneinputHeight
inputWidthoutputHeightoutputWidthc                 @   t          |           }|dk    r|dk    sJ |dk    r|dk    sJ |dk    r|dk    sJ | d         dk    o| d         dk    }|dk    r| d         dk    r|s|dk    r|r| d         dk    sJ |dz  |k    r	|dz  |k    sJ |dk    r|dk    sJ d S )Nr   r   r+   r,   r-   r   )rr   rs   rt   ru   rv   rw   rx   ry   rz   r{   r|   r}   r~   r   r   
valid_dimss                   r   pool2d_shape_checkr      s      u::D66b1fff66b1fffq==Y]]]*qQ058q=J		!HMM AII*IqQ	8 7d??rQw$.! 1 1 11 1 1r   kernel_sizepaddingc                    t          |          dk    st          |          dk    s
J d            |d         }t          |          dk    r|n|d         }t          |          dk    s0t          |          dk    st          |          dk    s
J d            t          |          dk    r|n|d         }t          |          dk    r|}	nt          |          dk    r|}	n|d         }	t          |          dk    st          |          dk    s
J d            |d         }
t          |          dk    r|
n|d         }t          |          dk    st          |          dk    s
J d            |d         }t          |          dk    r|n|d         }t          |           dk    st          |           d	k    sJ t          |           d	k    r| d
         nd}| d         }| d         }| d         }t          |||
|||          }t          ||||	||          }t          | ||||	|
||||||||           t          |           dk    r|||gS ||||gS )Nr   r+   zKmax_pool2d: kernel_size must either be a single int, or a tuple of two intsr   zOmax_pool2d: stride must either be omitted, a single int, or a tuple of two intszGmax_pool2d: padding must either be a single int, or a tuple of two intszHmax_pool2d: dilation must be either a single int, or a tuple of two intsr,   r-   r=   )r   rq   r   )rr   r   ri   r   rj   rk   rs   rt   ru   rv   rw   rx   ry   rz   nbatchr{   r|   r}   r~   r   s                       r   
max_pool2dr     s    {q  C$4$4$9$9$9U %:$99 
QB;1$$+a.Bv;;!s6{{a//3v;;!3C3C3CY 4D3CC 6{{aVAYB
6{{a	V		AYw<<1G 1 1 1Q !2 11 1:Dw<<1$$44'!*Dx==AX!!3!3!3R "4!33 I ]]a//		Xa[Iu::??c%jjAooo-e**//U2YYqF)K)KrJ'Rr9iXXL&z2tRIVVK



  " 5zzQ\;77\;??r   c                 2    t          | |||||          }||fS r"   )r   )rr   r   ri   r   rj   rk   r)   s          r   max_pool2d_with_indicesr   Y  s%     UK(I
N
NC:r   output_sizescale_factorsc                 N   g }|                     | d                    |                     | d                    ||
J d            |W|
J d            t          |          dk    sJ |                     |d                    |                     |d                    ||
J d            t          |          dk    sJ |                     t          | d         |d         z                       |                     t          | d         |d         z                       |S )Nr   r   z5Either output_size or scale_factors must be presentedz9Must specify exactly one of output_size and scale_factorsr+   r,   )r   r   int)rr   r   r   r)   s       r   upsample_nearest2dr   e  s?   
 CJJuQxJJuQx!4IIIIq$$G %$$ ;1$$$$

;q>"""

;q>""" ""G #"" =!!Q&&&&

3uQx-"2233444

3uQx-"2233444Jr   mat2c                     t          |           dk    s
J d            t          |          dk    s
J d            | d         |d         k    sJ | d         |d         gS )Nr+   zself must be a matrixzmat2 must be a matrixr   r   r   r(   r   s     r   mmr     sb    t99>>>2>>>t99>>>2>>>7d1gGT!Wr   tensorc                     t          |           dk    rt          |          dk    sJ | d         |d         k    sJ g }|S rm   r   )r(   r   r)   s      r   dotr     sJ    t99>>c&kkQ....7fQiCJr   vecc                     t          |           dk    rt          |          dk    sJ | d         |d         k    sJ | d         gS Nr+   r   r   r   )r(   r   s     r   mvr     sI    t99>>c#hh!mmm+7c!fG9r   lic                     t          |t          |           dz             }t          |           }|                    |d           |S rM   )rY   r   r3   insert)r   r?   r)   s      r   	unsqueezer     s?    
c"ggk
*
*C
))CJJsAJr   c                     g }t          t          |                     D ])}| |         dk    r|                    | |                    *|S rM   )r   r   r   )r   r)   r   s      r   squeeze_nodimr     sK    C3r77^^  a5A::JJr!uJr   c                    g }t          |t          |                     }t          t          |                     D ]K}||k    r(| |         dk    r|                    | |                    0|                    | |                    L|S rM   )rY   r   r   r   )r   r?   r)   wrapped_dimr   s        r   squeezer     s    C c"gg..K3r77^^  !uzz

2a5!!!JJr!uJr   rZ   c                    t          |          dk    r| S t          |          }t          t          |                    D ](}t          ||         t          |                     ||<   )g }t          t          |                     D ]I}| |         dk    r ||vr|                    | |                    .|                    | |                    J|S Nr   r   )r   r3   r   rY   r   )r   rZ   wrapped_dimsr   results        r   squeeze_dimsr     s    
4yyA~~	;;L3t99 C C(a#b''BBQF3r77^^ ! !a5A::$$be$$$MM"Q%    Mr   indexc                 n   t          |t          |                     }t          |          }t          |          dk    sJ |dk    s|t          |           k     sJ g }t          t          |                     D ]9}||k    r|                    |           |                    | |                    :|S rm   )rY   r   multiply_integersr   r   )r(   r?   r   rF   result_sizer   s         r   index_selectr     s    
c$ii
(
(Ce$$Eu::????!88sSYY&K3t99 ( (!88u%%%%tAw''''r   r=   weightindicespadding_idxscale_grad_by_freqsparsec                     t          |           dk    sJ t          |          dk    rt          | d|          S t          |          }|                    | d                    |S r   )r   r   r3   r   )r   r   r   r   r   r@   s         r   	embeddingr     sd     v;;!
7||qFAw///>>DKKq	Kr   c                      dS )Nl    rN   rN   r   r   max_intr     s    r   startendstepc                    t          |           }|dk    sJ t          ||          }||nd}||nt                      }|dk    sJ |t                      k    rd}|dk     r|| |         z  }|dk     r|| |         z  }|dk     rd}n|| |         k    r| |         }||k     r|}n|| |         k    r| |         }||z
  }t          |           }	||z   dz
  |z  |	|<   |	S r   )r   rY   r   r3   )
r(   r?   r   r   r   r   	start_valend_val	slice_lenr)   s
             r   slicer     s    t99D19999
d
#
#C*I_cc'))G!8888GII	1}}T#Y	{{491}}			T#Y		I		DI		s))#I
++CD 1$-CHJr   tensorsc                 :    | D ]}t          |          dk    sJ d S Nr   r   )r   r   s     r   check_cat_no_zero_dimr     s0      6{{Q r   tensor_sizesc                     d }|D ]@}t          |          dk    r|d         dk    s|t          | t          |                    }A|| }|S rm   )r   rY   )r?   r   out_dimr@   s       r   legacy_cat_wrap_dimr     s[    !G 9 9D		Q47a<<(c$ii88Nr   c                 N    t          |           dk    ot          |           dk    S r   rF   r   )r   s    r   should_skipr     s#    ==A2#f++"22r   firstsecond	dimensionc                     t          |           }t          |          }||k    s
J d            t          d|          D ]$}||k    r| |         ||         k    s
J d            %d S )Nz+Tensors must have same number of dimensionsr   z/Sizes of tensors must match except in dimension)r   r   )r   r   r   r   
first_dimssecond_dimsr?   s          r   check_cat_shape_except_dimr     s     UJf++K$$$&S$$$Q
##  ):,,,A -,, r   c                 z   t          |            t          ||           }t          |           dk    sJ d }| D ]}t          |          s|}|dgS d}t	          t          |                     D ]6}| |         }t          |          st          ||||           |||         z   }7t          |          }|||<   |S r   )r   r   r   r   r   r   r3   )r   r?   not_skipped_tensorr   cat_dim_sizer   r   s          r   catr   $  s    '"""
c7
+
+Cw<<!.2 ( (6"" 	(!'!s
L3w<<   6 66"" 	6&'963JJJ'&+5L*++K#Kr   c                 z    g }| D ]'}t          ||          }|                    |           (t          ||          S r"   )r   r   r   )r   r?   unsqueezed_tensorsr   
unsqueezeds        r   stackr   <  sN    *, . .vs++
!!*----!3'''r   c                    t          |           }|dk    sJ t          ||          }| |         }|| k     s||k    rJ |dk     r||z  }g }t          |          D ]#}||k    r|                    | |                    $|S r   )r   rY   r   r   )r(   r?   r   r   r@   r)   r   s          r   selectr   D  s    t99D19999
d
#
#C9D$/qyyC4[[    88JJtAwJr   tensor1tensor2c                    t          |           }t          |          }|dk    r|dk    rt          | |          S |dk    r|dk    rt          | |          S |dk    r2|dk    r,t          t	          t          | d          |          d          S |dk    r|dk    rt	          | |          S |dk    r|dk    r|dk    r| d         nd}g }t          |dz
            D ]}|                    | |                    |d         }g }t          |dz
            D ]}|                    ||                    t          ||          }	|	}
|dk    r|
                    |           |dk    r|
                    |           |
S J d            )Nr   r+   r   r   r=   Fz0both  arguments to matmul need to be at least 1D)	r   r   r   r   r   r   r   r   r   )r   r   dim_tensor1dim_tensor2nbatch_tensor1r   pbatch_tensor2expand_batch_portionoutput_shapes              r   matmulr   S  s   g,,Kg,,KaK1,,7G$$$			kQ..'7###			kQ..r)GQ//991===			kQ..'7###			kQ.. '??GBKK#%{Q'' 	- 	-A  ,,,,BK#%{Q'' 	- 	-A  ,,,,  )FF ,??"""??"""HHHHur   c                     t          |           dk    sJ t          |           }|dk    rg }|S |dk    r	| d         gS | d         | d         gS )Nr+   r   r   r   )r(   self_lenr)   s      r   tr   |  s[    t99>>>>4yyH1}}
	QQyQa!!r   dim0dim1c                 t   t          |           }t          ||          }t          ||          }||k    rt          |           S g }t          |          D ]a}||k    r|                    | |                    $||k    r|                    | |                    F|                    | |                    b|S r"   )r   rY   r3   r   r   )r(   r   r   ndimsr)   r   s         r   	transposer     s    IIE$&&D$&&Dt||T{{C5\\    99JJtDz""""$YYJJtDz""""JJtAwJr   biasc                 p    t          | t          |                    }|t          ||          |k    sJ |S r"   )r   r   r   )rr   r   r   r)   s       r   linearr     s=    
&		
"
"Cs##s****Jr   mat1betaalphac                 >    t          | t          ||                    S r"   )r   r   )r(   r   r   r   r   s        r   addmmr     s    T2dD>>***r   arrayc                 $    d}| D ]
}|dk     rd}|S )NFr   TrN   )r   non_negativevals      r   check_non_negativer     s+    L    77Lr   weight_sizesgroupsc                    t          |           }t          |          }t          |          rJ t          |          rJ ||k    sJ |d         |k    sJ |d         |z  dk    sJ | d         |d         |z  k    sJ |'t          |          dk    r|d         |d         k    sJ t          d|          D ]7}	| |	         d||	dz
           z  z   ||	dz
           ||	         dz
  z  dz   k    sJ 8d S Nr   r   r+   )r   r   r   )
rr   r   r   ri   r   rj   r   k
weight_dimr   s
             r   check_shape_forwardr    s<    	E

A\""J "'*****!&)))))?????f$$$$Of$****8|A/////<CIINNtAw,q//I/I/IJ1a[[ 
 
a1wq1u~--QUO|A23a7
 
 
 
 

 
r   
input_sizeweight_sizec           	         t          | ||||||           t          |          dk    }t          |           }g }	d}
d}|	                    | |
                    |	                    ||                    t          d|          D ]^}|r||dz
           nd}|||         dz
  z  dz   }|	                    | |         d||dz
           z  z   |z
  ||dz
           z  dz              _|	S )Nr   r+   r   )r  r   r   r   )r  r  r   ri   r   rj   r   has_dilationr?   r   input_batch_size_dimweight_output_channels_dimd	dilation_kernels                  r   conv_output_sizer    s!    Kvw&   x==1$L
j//CK!"z"67888{#=>???1c]] 
 
'3:HQUOO	k!nq01A5]a'!a%.01F:va!e}LqP	
 	
 	
 	
 r   c           	          t          |          dk    sJ t          |           dk    sJ t          | ||||||          S )Nr,   r   r  rr   r   r   ri   r   rj   r   s          r   conv1dr    H     v;;!u::????E64(FSSSr   c           	          t          |          dk    sJ t          |           dk    sJ t          | ||||||          S )Nr-   r  r  s          r   conv2dr    r  r   grad_outputbiasesc                 N    t          |          t          |          | d         gfS rM   r5   )r  rr   r   r  s       r   conv_backwardsr    s$     <<vQ(888r   r   output_paddingc                    |ddg}|ddg}|ddg}|ddg}t          |          dk    }t          |           }	g }
d}d}|
                    | |                    |
                    ||         |z             t          d|	          D ]j}|r||dz
           nd}|||         dz
  z  }|
                    | |         dz
  ||dz
           z  d||dz
           z  z
  |z   ||dz
           z   dz              k|
S )Nr   r   r+   r   r   r   )rr   r   r   ri   r   r  r   rj   r	  r?   r   r
  r  r  r  r  s                   r   conv_transpose2d_inputr    sY    ~Qa&Qq6x==1$L
e**CK!"u12333v89FBCCC1c]] 	
 	
'3:HQUOO	fQi!m,1X\VAE]*'!a%. ! QU#$ 		
 	
 	
 	
 r   
transposedc	                    t          |          dk    }	t          |          dk    }
t          |           }g }d}|rdnd}|                    | |                    |r|                    ||         |z             n|                    ||                    t          d|          D ]}|	r||dz
           nd}|
r||dz
           nd}|rQ|||         dz
  z  }|                    | |         dz
  ||dz
           z  d||dz
           z  z
  |z   |z   dz              s|||         dz
  z  dz   }|                    | |         d||dz
           z  z   |z
  ||dz
           z  dz              |S r  r  )rr   r   r   ri   r   rj   r  r  r   r	  has_output_paddingr?   r   r
  r  r  r  output_padding_r  s                      r   conv_forwardsr#  7  s    x==1$L^,,q0
e**CK&0!7au12333 ?6"<=FGGGG6"<=>>>1c]]  '3:HQUOO	3EL.Q//1 	&)a-0FqAA.ga!en$% "" 	    &)a-014FqQQ/069fQUmKaO    r   	benchmarkdeterministiccudnn_enabled
allow_tf32c                 0    t          | ||||||||	  	        S r"   )r#  )rr   r   r   ri   r   rj   r  r  r   r$  r%  r&  r'  s                r   _conv_forwardsr)  b  s1     
 
 
r   running_meanrunning_vartrainingmomentumepsc	                 >    g }	| D ]}
|	                     |
           |	S r"   r2   )rr   r   r   r*  r+  r,  r-  r.  r&  r)   r/   s              r   
batch_normr0  ~  s2     C  

4Jr   c           	          t          |          dk    sJ t          |           dk    sJ t          | ||||||          S )N   r  r  s          r   conv3dr3    r  r   Tdim_post_exprwrap_scalarc                 `    |dk    r|sJ d}| }|dz
  }| |k     s| |k    rJ | dk     r| |z  } | S r   rN   )r?   r4  r5  minr   s        r   rY   rY     s\    {.C
!
Cc		S3YYY'
Qww}Jr   c                 
    g }|S r"   rN   )rr   r)   s     r   zero_dim_tensorr9    s    CJr   c                     d}| D ]}||z  }|S rM   rN   )r   r)   r/   s      r   r   r     s&    
C  DjJr   inp1inp2inp3c                 V    | dk    sJ t          t          j        |                     gS r   r   mathceil)r   rC   r;  r<  r=  s        r   
arange_endrB    s(    !8888	#  r   c                 l    |dk    sJ || k    sJ t          t          j        || z
                      gS r   r?  )r   r   rC   r;  r<  r=  s         r   arange_startrD    s=     !8888%<<<<	#+&&''((r   c                     |dk    sJ |dk     r	| |k    sJ n|| k    sJ t          t          j        || z
  |z                      gS r   r?  )r   r   r   rC   r;  r<  r=  s          r   arange_start_steprF    sZ     19999axx|||||e||||	3;$.//0011r   c                    t          |           t          |          k    sJ t          |          }g }g }t          |          D ]H}t          ||         |          }|                    |           |                    | |                    It          d|          D ](}t          |          D ]}||         ||         k    sJ )|S rM   )r   r   rY   r   )rr   rZ   r   	seen_dimsnewSizesr   r?   js           r   permuterK    s    u::T""""t99DIH4[[ $ $T!Wd++c
####1d^^ 0 0q 	0 	0AQ<9Q</////	0Or   sourcedestinationc                 N   t          |           }|dk    r| S g }g }t          t          |                    D ]T}|                    t          ||         |                     |                    t          ||         |                     Ud t          |          D             }d t          |          D             }d t          |          D             }	t          t          |                    D ])}||         |||         <   d|||         <   d|	||         <   *g }
g }|D ]}|dk    r|
                    |           |	D ]}|dk    r|                    |           |t          |          z
  }t          |          D ]}|
|         |||         <   t	          | |          S )Nr   c                     g | ]}d S r=   rN   .0r   s     r   
<listcomp>zmovedim.<locals>.<listcomp>  s    )))AR)))r   c                     g | ]}|S rN   rN   rQ  s     r   rS  zmovedim.<locals>.<listcomp>      +++a+++r   c                     g | ]}|S rN   rN   rQ  s     r   rS  zmovedim.<locals>.<listcomp>  rU  r   r=   )r   r   r   rY   rK  )r(   rL  rM  self_dimnormalized_srcnormalized_dstr   ordersrc_dimsdst_dimssource_dimsdestination_dimselerest_dims                 r   movedimra    s   4yyH1}} "N "N3v;; H HnVAYAABBBn[^XFFGGGG))x)))E++5??+++H++5??+++H3v;; ) )#1!#4nQ &("#&("##K"$ $ $"99s### ) )"99##C(((#f++%H8__ 4 4%0^q!""4r   	start_dimend_dimc                 H   t          |t          |                     }t          |t          |                     }||k    sJ t          |           dk    rdgS ||k    rg }| D ]}|                    |           |S d}t          ||dz             D ]}|| |         z  }g }t          |          D ]}|                    | |                    |                    |           t          |dz   t          |                     D ]}|                    | |                    |S r   )rY   r   r   r   )rr   rb  rc  r)   r/   slice_numelr   r.   s           r   flattenrf    sH   y#e**55IWc%jj11G
5zzQs
G 	 	DJJt
K9gk**    uQx E9  U1X	LL7Q;E

++  U1XLr   c                 $    dt          |           gS r   r   rr   s    r   nonzero_lower_boundri    s    s5zz?r   c                 >    t          |           t          |           gS r"   r   rh  s    r   nonzero_upper_boundrk    s    %LL#e**%%r   keepdimc                     t          |t          |                     }g }t          |           D ]8\  }}||k    r|r|                    d           #|                    |           9|S rM   )rY   r   	enumerater   )r(   r?   rl  r)   r   rW  s         r   _reduce_along_dimro    sp    
c$ii
(
(CC  ! !888 

1JJx    Jr   c                 ,    |g S t          | ||          S r"   )ro  )r(   r?   rl  s      r   argmaxrq  +  s      {	T3000r   c                    t          |           dk    s
J d            t          |          dk    s
J d            | d         |d         k    s
J d            | d         |d         k    s
J d            | d         | d         |d         gS )Nr,   zbmm only supports 3D tensorsr   zmismatching batch dimensionr+   r   z!mismatching contracting dimensionr   r   s     r   bmmrs  3  s    t99>>>9>>>t99>>>9>>>7d1g<7d1gBGT!Wd1g&&r   c                 "    t          |           gS r"   r   r6   s    r   _shape_as_tensorru  ;  s    II;r   r  c                     t          |           dk    rg }n9|| |         k    sJ d| d| d| |                      t          |           }|||<   ||fS )Nr   zk (z) is too big for dimension z	 of size )r   r3   )r(   r  r?   r   s       r   topkrw  ?  so    
4yyA~~DI~~~I!IIIId3iII ~~ ts6>r   target	reductionc                 F   t          |           }t          |          }d|cxk     rdk    sn J |dk    sJ |dk    o|dk    }|s| d         |d         k    sJ | d         }g }|!t          |          dk    r|d         |k    sJ |dk    r|dk    r
| d         g}	n|}	|	|fS )Nr   r+   r   r=   r   )
r(   rx  r   ry  rW  
target_dimno_batch_dim	n_classesscalar_shapereduction_shapes
             r   nll_loss_forwardr  K  s     4yyHVJx1????q=4Z1_L1DGvay0001RI L>c&kkQ..6!9	3I3I3IJA~~(a--7)&L((r   normalized_shapec                 <   g }t          |           t          |          z
  }|dk    sJ t          |          D ]}|                    | |                    t          |t          |                     D ]}|                    d           t          |           ||fS r   )r   r   r   r3   )rr   r  r  num_unreduced_dimensionsr   s        r   native_layer_normr  _  s     "$O"5zzC0@,A,AA#q((((+,, ) )uQx((((+SZZ88 " "q!!!!<</99r   c                 D    |r
| d         g}ndg}t          |           ||fS rm   r5   )rr   r   r   r*  r+  r,  _sizes          r   native_batch_normr  l  s3      q
<<%%r   c                 <    | d         g}t          |           ||dgfS rm   r5   )rr   r   r   r*  r+  r  s         r   _batch_norm_with_updater  {  s&     1XJE<<s**r           ignore_indexlabel_smoothingc                 6    t          | |||          d         }|S r   )r  )r(   rx  r   ry  r  r  result_shapes          r   cross_entropy_lossr    s"     $D&&)DDQGLr   shape_compute_graph_mappingbounded_compute_graph_mappingscript_func_mapfuncc                 |   | t           vrt          j                            |           }t          j                            |j                   t          d          D ]J}t          j                            |j                   t          j        	                    |j                   K|t           | <   t           |          S )Nr+   )
r  torchjitscript_C_jit_pass_inlinegraphr   _jit_pass_peephole_jit_pass_constant_propagation)r  scripted_func_s      r   process_funcr    s    ?""	((..!!-"5666q 	I 	IAH''(;<<<H33M4GHHHH -4  r   operator_schemac                 4    t          |          t          | <   d S r"   )r  r  )r  r  s     r   add_shape_compute_mappingr    s     4@3E3E000r   lower_bound_funcupper_bound_funcc                 V    t          |          t          |          f}|t          | <   d S r"   )r  r  )r  r  r  fnss       r   add_bounded_compute_mappingr    s1     ())<8H+I+I
JC58!/222r   z^aten::contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a)zFaten::rsub.Tensor(Tensor self, Scalar other, Scalar alpha=1) -> Tensorz:aten::dropout(Tensor input, float p, bool train) -> TensorzDaten::adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensorz,prim::NumToTensor.Scalar(Scalar a) -> Tensorz(prim::NumToTensor.bool(bool a) -> Tensorzuaten::zeros(int[] size, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None) -> (Tensor)z{aten::to.dtype(Tensor(a) self, int dtype, bool non_blocking=False, bool copy=False, int? memory_format=None) -> (Tensor(a))zvaten::arange(Scalar end, *, int? dtype=None, int? layout=None, Device? device=None, bool? pin_memory=None) -> (Tensor)zaten::arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensorzaten::arange.start_step(Scalar start, Scalar end, Scalar step, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensorz*aten::squeeze(Tensor(a) self) -> Tensor(a)z7aten::squeeze.dim(Tensor(a) self, int dim) -> Tensor(a)z:aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a)z5aten::unsqueeze(Tensor(a) self, int dim) -> Tensor(a)zfaten::slice.Tensor(Tensor(a) self, int dim=0, int? start=None, int? end=None, int step=1) -> Tensor(a)zAaten::select.int(Tensor(a) self, int dim, int index) -> Tensor(a)z@aten::index_select(Tensor self, int dim, Tensor index) -> Tensorzaten::layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> TensorzIaten::softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensorzhaten::_no_grad_embedding_renorm_(Tensor weight, Tensor input, float max_norm, float norm_type) -> Tensorzgaten::embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!)z~aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensorz,aten::mm(Tensor self, Tensor mat2) -> Tensorz/aten::dot(Tensor self, Tensor tensor) -> Tensorz+aten::mv(Tensor self, Tensor vec) -> Tensorz1aten::matmul(Tensor self, Tensor other) -> TensorzFaten::linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensorzaten::max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensorzaten::max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)z$aten::t(Tensor(a) self) -> Tensor(a)zDaten::transpose.int(Tensor(a) self, int dim0, int dim1) -> Tensor(a)zaten::conv1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] dilation=1, int groups=1) -> Tensorzaten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensorzaten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensorzaten::conv3d(Tensor input, Tensor weight, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, int groups=1) -> Tensorzaten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, int[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)zaten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensorzaten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensorzaten::conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> TensorzVaten::flatten.using_ints(Tensor(a) self, int start_dim=0, int end_dim=-1) -> Tensor(a)z0aten::cat(Tensor[] tensors, int dim=0) -> Tensorz2aten::stack(Tensor[] tensors, int dim=0) -> Tensorz6aten::permute(Tensor(a) self, int[] dims) -> Tensor(a)zSaten::movedim.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a)z3aten::view(Tensor(a) self, int[] size) -> Tensor(a)z:aten::expand_as(Tensor(a) self, Tensor other) -> Tensor(a)zMaten::expand(Tensor(a) self, int[] size, *, bool implicit=False) -> Tensor(a)zaaten::mean.dim(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensorzhaten::sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> TensorzZaten::max.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)z<aten::mean(Tensor self, *, ScalarType? dtype=None) -> Tensorz;aten::sum(Tensor self, *, ScalarType? dtype=None) -> Tensorz^aten::addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensorzbaten::upsample_nearest2d.vec(Tensor input, int[]? output_size, float[]? scale_factors) -> (Tensor)z_aten::quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensorzraten::quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensorz'aten::dequantize(Tensor self) -> TensorzNquantized::add(Tensor qa, Tensor qb, float scale, int zero_point) -> Tensor qczFaten::argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensorz-aten::bmm(Tensor self, Tensor mat2) -> Tensorz-aten::_shape_as_tensor(Tensor self) -> Tensorzraten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)zaten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight)zaten::native_layer_norm(Tensor input, int[] normalized_shape, Tensor? weight, Tensor? bias, float eps) -> (Tensor, Tensor, Tensor)zaten::native_batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)zaten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)zaten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)z_batch_norm_with_update(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor)zaten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> TensorzCaten::lerp.Tensor(Tensor self, Tensor end, Tensor weight) -> TensorzMaten::where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> TensorzQaten::add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)z&aten::nonzero(Tensor self) -> (Tensor))r=   FF)NNNNr   N)T)NFrP  )Nr   r  r  )ir@  typingr   r   r   r   r   r   r	   r   floatnumberr  rX   r   r%   r'   r0   r3   r7   r:   rB   rE   rK   rF   rP   boolrS   r^   r`   rd   ro   rq   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r  r  r  r  r  r  r#  r)  r0  r3  rY   r9  r   rB  rD  rF  rK  ra  rf  ri  rk  ro  rq  rs  ru  tuplerw  r  r  r  r  r  r  ScriptFunctionScriptFnr  dictstr__annotations__r  r  r  r  r  rN   r   r   <module>r     s    D D D D D D D D D D D D D D D D D D 
sEz	$ c tCy    0)tCy )T#Y )49 ) ) ) )49  c    d3i d3i    S	    S	    c tCy    (c 49    ,DI d3i s    49 S T#Y    .c    /tCy /c / / / / LQ   $s) DI D    
s)'S	2>BHK   ,$s) #     s s      	
      6  	
     2922 	2 		2
 	2 2 2 2 2 2 2 2 2 2 2 2 2DC@9C@cC@ IC@ #Y	C@
 3iC@ C@ C@ C@ C@L	9	c	 I	 #Y		
 3i	 	 	 	 	9$s)$ DK(   >T#Y d3i    d3i c    T#Y T#Y    $s) #    d3i    	S	 	 	 	 	 	T#Y d3i     tCy s 49    " $ I#Y  	
      
s)&.sm:B3-OR   :4S	?    
S T#Y    3S	 3 3 3 3
9
"3i
47
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d3i s    0(4S	? ( ( ( ( (c  S    &IDI &IS	 &I &I &I &IR	"DI 	" 	" 	" 	"DI S     "$s) T#Y htCy6I    +S	 +c +$s) +3 +s + + + +d3i D    
9
s)
 49

 I	

 #Y
 3i
 
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>S	c 49
 I	
 #Y 3i    <T9TIT 49
T I	T
 #YT 3iT T T T TT9TIT 49
T I	T
 #YT 3iT T T T T9c999 I9 T#Y	9 9 9 9 !%"&#'*.$($ $9$I$ 49
$ T#Y	$
 d3i $ T#Y'$ $ tCy!$ 
#Y$ $ $ $N(9(I( 49
( I	(
 #Y( 3i( ( I( ( 
#Y( ( ( (V9I 49
 I	
 #Y 3i  I      
#Y   89T#Y 49
 49%	
 $s)$   
    "T9TIT 49
T I	T
 #YT 3iT T T T T	 	 	C 	d 	 	 	 	3    
$s)    !F !# !S ! !3 ! ! ! !
)))&))14)<?)GJ) ) ) )222&,2472?B2JM2UX2 2 2 249 DI     $s)  T#Y  T#Y  4PS9        B49  s    4tCy    &tCy & & & &	DI 	C 	$ 	 	 	 	 AF1 1
s)1"3-19=1	#Y1 1 1 1'd3i 'tCy 'T#Y ' ' ' '49 c    	 	tCy 	S 	s 	E$s)T#Y:N4O 	 	 	 	)
s))!#Y)08c0C)PS)
49d3i ) ) ) )(
:9
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49d3ic*+
: 
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: 
:&9&T#Y& 49
& 49%	&
 $s)$& & 49d3ic*+& & & &+9+T#Y+ 49
+ 49%	+
 $s)$+ 49d3icDI56+ + + + #' 	 	
s)	I	 T#Y	 		
 	 	 
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  OQV    n	    m	     E    H" M M M  KS Q Q Q  G L L L  Mv V V V  Lf     O     f    @! D D D  JI     Q
     Q
     v     Q
     v     m     w     z    \    Lc R R R  NPU V V V  <g    Y    OQU V V V  @&    S    g    n    `    BO    A?    d	    h    e	    x	    CU K K K  T    Lf    I3 O O O  35E    x     R     I     {     @     I     z  
   c    I    S    W    ,.ACV    r   