
    i[              	          d Z ddlZddlZddlmZ ddl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 dd
lmZ ddlmZ ddlmZmZmZ ddlmZ  ej8                  e      Ze ed       G d de                    Zd Z d Z!dFdejD                  de#de$dejD                  fdZ% G d dejL                        Z' G d dejL                        Z( G d dejL                        Z) G d  d!ejL                        Z* G d" d#ejL                        Z+ G d$ d%ejL                        Z, G d& d'ejL                        Z- G d( d)ejL                        Z. G d* d+ejL                        Z/ G d, d-ejL                        Z0 G d. d/ejL                        Z1 G d0 d1e      Z2 G d2 d3ejL                        Z3e G d4 d5e             Z4e G d6 d7e4             Z5 G d8 d9ejL                        Z6 G d: d;ejL                        Z7 G d< d=ejL                        Z8 G d> d?ejL                        Z9 G d@ dAejL                        Z: edB       G dC dDe4             Z;g dEZ<y)Gz"PyTorch Swin2SR Transformer model.    N)	dataclass)nn   )initialization)ACT2FN)GradientCheckpointingLayer)BaseModelOutputImageSuperResolutionOutput)PreTrainedModel)meshgrid)ModelOutputauto_docstringlogging   )Swin2SRConfigzQ
    Swin2SR encoder's outputs, with potential hidden states and attentions.
    )custom_introc                       e Zd ZU dZej
                  dz  ed<   dZeej
                     dz  ed<   dZ	eej
                     dz  ed<   y)Swin2SREncoderOutputNlast_hidden_statehidden_states
attentions)
__name__
__module____qualname__r   torchFloatTensor__annotations__r   tupler        v/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/transformers/models/swin2sr/modeling_swin2sr.pyr   r   $   sN     37u((4/659M5**+d2926Je''(4/6r    r   c                     | j                   \  }}}}| j                  |||z  |||z  ||      } | j                  dddddd      j                         j                  d|||      }|S )z2
    Partitions the given input into windows.
    r   r   r            shapeviewpermute
contiguous)input_featurewindow_size
batch_sizeheightwidthnum_channelswindowss          r!   window_partitionr3   1   s}     /<.A.A+J|!&&Fk);8Lk[gM ##Aq!Q15@@BGGKYdfrsGNr    c                     | j                   d   }| j                  d||z  ||z  |||      } | j                  dddddd      j                         j                  d|||      } | S )z?
    Merges windows to produce higher resolution features.
    r&   r   r   r   r#   r$   r%   r'   )r2   r-   r/   r0   r1   s        r!   window_reverser5   >   sn     ==$Lll2v4e{6JKYdfrsGooaAq!Q/::<AA"feUabGNr    input	drop_probtrainingreturnc                    |dk(  s|s| S d|z
  }| j                   d   fd| j                  dz
  z  z   }|t        j                  || j                  | j
                        z   }|j                          | j                  |      |z  }|S )zc
    Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).

            r   r   )r   )dtypedevice)r(   ndimr   randr<   r=   floor_div)r6   r7   r8   	keep_probr(   random_tensoroutputs          r!   	drop_pathrE   I   s    
 CxII[[^

Q 77E

5ELL YYMYYy!M1FMr    c                   x     e Zd ZdZd	dedz  ddf fdZdej                  dej                  fdZde	fdZ
 xZS )
Swin2SRDropPathzXDrop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).Nr7   r9   c                 0    t         |           || _        y N)super__init__r7   )selfr7   	__class__s     r!   rK   zSwin2SRDropPath.__init__\   s    "r    r   c                 D    t        || j                  | j                        S rI   )rE   r7   r8   rL   r   s     r!   forwardzSwin2SRDropPath.forward`   s    FFr    c                      d| j                    S )Nzp=)r7   rL   s    r!   
extra_reprzSwin2SRDropPath.extra_reprc   s    DNN#$$r    rI   )r   r   r   __doc__floatrK   r   TensorrP   strrS   __classcell__rM   s   @r!   rG   rG   Y   sG    b#%$, #$ #GU\\ Gell G%C %r    rG   c                   f     e Zd ZdZ fdZdej                  dz  deej                     fdZ	 xZ
S )Swin2SREmbeddingsz?
    Construct the patch and optional position embeddings.
    c                 x   t         |           t        |      | _        | j                  j                  }|j
                  r=t        j                  t        j                  d|dz   |j                              | _        nd | _        t        j                  |j                        | _        |j                  | _        y )Nr   )rJ   rK   Swin2SRPatchEmbeddingspatch_embeddingsnum_patchesuse_absolute_embeddingsr   	Parameterr   zeros	embed_dimposition_embeddingsDropouthidden_dropout_probdropoutr-   )rL   configr_   rM   s      r!   rK   zSwin2SREmbeddings.__init__l   s     6v >++77))')||EKK;QR?TZTdTd4e'fD$'+D$zz&"<"<=!--r    pixel_valuesNr9   c                     | j                  |      \  }}| j                  || j                  z   }| j                  |      }||fS rI   )r^   rd   rg   )rL   ri   
embeddingsoutput_dimensionss       r!   rP   zSwin2SREmbeddings.forwardz   sN    (,(=(=l(K%
%##/#d&>&>>J\\*-
,,,r    )r   r   r   rT   rK   r   r   r   rV   rP   rX   rY   s   @r!   r[   r[   g   s4    .-E$5$5$< -u||AT -r    r[   c                   n     e Zd Zd fd	Zdej
                  dz  deej                  ee   f   fdZ	 xZ
S )r]   c                    t         |           |j                  }|j                  |j                  }}t        |t        j                  j                        r|n||f}t        |t        j                  j                        r|n||f}|d   |d   z  |d   |d   z  g}|| _	        |d   |d   z  | _
        t        j                  ||j                  ||      | _        |r%t        j                  |j                        | _        y d | _        y )Nr   r   )kernel_sizestride)rJ   rK   rc   
image_size
patch_size
isinstancecollectionsabcIterablepatches_resolutionr_   r   Conv2d
projection	LayerNorm	layernorm)rL   rh   normalize_patchesr1   rq   rr   rw   rM   s          r!   rK   zSwin2SRPatchEmbeddings.__init__   s    ''!'!2!2F4E4EJ
#-j+//:R:R#SZZdfpYq
#-j+//:R:R#SZZdfpYq
(mz!}<jmzZ[}>\]"4-a03Ea3HH))L&2B2BPZcmn;Lf&6&67RVr    rk   Nr9   c                     | j                  |      }|j                  \  }}}}||f}|j                  d      j                  dd      }| j                  | j	                  |      }||fS )Nr#   r   )ry   r(   flatten	transposer{   )rL   rk   _r/   r0   rl   s         r!   rP   zSwin2SRPatchEmbeddings.forward   so    __Z0
(..1fe#UO''*44Q:
>>%
3J,,,r    )T)r   r   r   rK   r   r   r   rV   intrP   rX   rY   s   @r!   r]   r]      s<    W	-%"3"3d": 	-uU\\SXY\S]E]?^ 	-r    r]   c                   (     e Zd ZdZ fdZd Z xZS )Swin2SRPatchUnEmbeddingszImage to Patch Unembeddingc                 D    t         |           |j                  | _        y rI   )rJ   rK   rc   )rL   rh   rM   s     r!   rK   z!Swin2SRPatchUnEmbeddings.__init__   s    ))r    c                     |j                   \  }}}|j                  dd      j                  || j                  |d   |d         }|S )Nr   r#   r   )r(   r   r)   rc   )rL   rk   x_sizer.   height_widthr1   s         r!   rP   z Swin2SRPatchUnEmbeddings.forward   sO    1;1A1A.
L,))!Q/44ZQWXYQZ\bcd\ef
r    r   r   r   rT   rK   rP   rX   rY   s   @r!   r   r      s    %*
r    r   c            	            e Zd ZdZej
                  fdee   dedej                  ddf fdZ	d Z
d	ej                  d
eeef   dej                  fdZ xZS )Swin2SRPatchMerginga'  
    Patch Merging Layer.

    Args:
        input_resolution (`tuple[int]`):
            Resolution of input feature.
        dim (`int`):
            Number of input channels.
        norm_layer (`nn.Module`, *optional*, defaults to `nn.LayerNorm`):
            Normalization layer class.
    input_resolutiondim
norm_layerr9   Nc                     t         |           || _        || _        t	        j
                  d|z  d|z  d      | _         |d|z        | _        y )Nr$   r#   Fbias)rJ   rK   r   r   r   Linear	reductionnorm)rL   r   r   r   rM   s       r!   rK   zSwin2SRPatchMerging.__init__   sI     01s7AG%@q3w'	r    c                     |dz  dk(  xs |dz  dk(  }|r.ddd|dz  d|dz  f}t         j                  j                  ||      }|S )Nr#   r   r   )r   
functionalpad)rL   r,   r/   r0   
should_pad
pad_valuess         r!   	maybe_padzSwin2SRPatchMerging.maybe_pad   sU    qjAo:519>
Q519a!<JMM--mZHMr    r,   input_dimensionsc                    |\  }}|j                   \  }}}|j                  ||||      }| j                  |||      }|d d dd ddd dd d f   }|d d dd ddd dd d f   }	|d d dd ddd dd d f   }
|d d dd ddd dd d f   }t        j                  ||	|
|gd      }|j                  |dd|z        }| j                  |      }| j                  |      }|S )Nr   r#   r   r&   r$   )r(   r)   r   r   catr   r   )rL   r,   r   r/   r0   r.   r   r1   input_feature_0input_feature_1input_feature_2input_feature_3s               r!   rP   zSwin2SRPatchMerging.forward   s   ((5(;(;%
C%**:vulS}feD'14a4Aq(89'14a4Aq(89'14a4Aq(89'14a4Aq(89		?O_Ve"fhjk%**:r1|;KL}5		-0r    )r   r   r   rT   r   rz   r   r   ModulerK   r   r   rV   rP   rX   rY   s   @r!   r   r      sr    
 XZWcWc (s (# (299 (hl (U\\ U3PS8_ Y^YeYe r    r   c            
            e Zd Zddgf fd	Z	 	 d
dej
                  dej                  dz  dedz  deej
                     fdZ	d	 Z
 xZS )Swin2SRSelfAttentionr   c           
         t         |           ||z  dk7  rt        d| d| d      || _        t	        ||z        | _        | j                  | j
                  z  | _        t        |t        j                  j                        r|n||f| _        || _        t        j                  t        j                   dt        j"                  |ddf      z              | _        t        j&                  t        j(                  ddd	
      t        j*                  d	      t        j(                  d|d
            | _        | j/                         \  }}| j1                  d|d       | j1                  d|d       t        j(                  | j                  | j                  |j2                  
      | _        t        j(                  | j                  | j                  d
      | _        t        j(                  | j                  | j                  |j2                  
      | _        t        j:                  |j<                        | _        y )Nr   zThe hidden size (z6) is not a multiple of the number of attention heads ()
   r   r#   i   Tr   inplaceFrelative_coords_table
persistentrelative_position_index) rJ   rK   
ValueErrornum_attention_headsr   attention_head_sizeall_head_sizers   rt   ru   rv   r-   pretrained_window_sizer   ra   r   logoneslogit_scale
Sequentialr   ReLUcontinuous_position_bias_mlpcreate_coords_table_and_indexregister_bufferqkv_biasquerykeyvaluere   attention_probs_dropout_probrg   )	rL   rh   r   	num_headsr-   r   r   r   rM   s	           r!   rK   zSwin2SRSelfAttention.__init__   s   ?a#C5(^_h^iijk  $- #&sY#7 !558P8PP%k;??3K3KLKS^`kRl 	 '=#<<		"uzz9aQRBS7T2T(UV,.MMIIa4("''$*?3PY`eAf-
) :>9[9[9]6646KX]^68O\abYYt1143E3EFOO\
99T//1C1C%PYYt1143E3EFOO\
zz&"E"EFr    Nr   attention_maskoutput_attentionsr9   c                 R   |j                   \  }}}| j                  |      j                  |d| j                  | j                        j                  dd      }| j                  |      j                  |d| j                  | j                        j                  dd      }| j                  |      j                  |d| j                  | j                        j                  dd      }	t        j                  j                  |d      t        j                  j                  |d      j                  dd      z  }
t        j                  | j                  t        j                  d            j!                         }|
|z  }
| j#                  | j$                        j                  d| j                        }|| j&                  j                  d         j                  | j(                  d   | j(                  d   z  | j(                  d   | j(                  d   z  d      }|j+                  ddd      j-                         }d	t        j.                  |      z  }|
|j1                  d      z   }
||j                   d   }|
j                  ||z  || j                  ||      |j1                  d      j1                  d      z   }
|
|j1                  d      j1                  d      z   }
|
j                  d| j                  ||      }
t        j                  j3                  |
d      }| j5                  |      }t        j6                  ||	      }|j+                  dddd
      j-                         }|j9                         d d | j:                  fz   }|j                  |      }|r||f}|S |f}|S )Nr&   r   r#   )r   g      Y@)maxr      r   )r(   r   r)   r   r   r   r   r   r   r   	normalizer   clampr   mathr   expr   r   r   r-   r*   r+   sigmoid	unsqueezesoftmaxrg   matmulsizer   )rL   r   r   r   r.   r   r1   query_layer	key_layervalue_layerattention_scoresr   relative_position_bias_tablerelative_position_bias
mask_shapeattention_probscontext_layernew_context_layer_shapeoutputss                      r!   rP   zSwin2SRSelfAttention.forward  sx    )6(;(;%
CJJ}%T*b$":":D<T<TUYq!_ 	 HH]#T*b$":":D<T<TUYq!_ 	 JJ}%T*b$":":D<T<TUYq!_ 	 ==22;B2G"--JaJa2 Kb K

)B
 kk$"2"28LMQQS+k9'+'H'HIcIc'd'i'i(((
$ ">d>Z>Z>_>_`b>c!d!i!iQ$"2"21"55t7G7G7JTM]M]^_M`7`bd"
 "8!?!?1a!H!S!S!U!#emm4J&K!K+.D.N.Nq.QQ%'--a0J/44j(*d6N6NPSUX ((+55a8 9  0.2J2J12M2W2WXY2ZZ/44R9Q9QSVX[\ --//0@b/I ,,7 _kB%--aAq9DDF"/"4"4"6s";t?Q?Q>S"S%**+BC6G=/2 O\M]r    c                    t        j                  | j                  d   dz
   | j                  d   t         j                        j	                         }t        j                  | j                  d   dz
   | j                  d   t         j                        j	                         }t        j
                  t        ||gd            j                  ddd      j                         j                  d      }| j                  d   dkD  rO|d d d d d d dfxx   | j                  d   dz
  z  cc<   |d d d d d d dfxx   | j                  d   dz
  z  cc<   n`| j                  d   dkD  rN|d d d d d d dfxx   | j                  d   dz
  z  cc<   |d d d d d d dfxx   | j                  d   dz
  z  cc<   |dz  }t        j                  |      t        j                  t        j                  |      dz         z  t        j                  d      z  }|j                  t!        | j"                  j%                               j&                        }t        j                  | j                  d         }t        j                  | j                  d         }t        j
                  t        ||gd            }t        j(                  |d      }|d d d d d f   |d d d d d f   z
  }|j                  ddd      j                         }|d d d d dfxx   | j                  d   dz
  z  cc<   |d d d d dfxx   | j                  d   dz
  z  cc<   |d d d d dfxx   d| j                  d   z  dz
  z  cc<   |j+                  d	      }	||	fS )
Nr   r   r<   ij)indexingr#      g      ?r&   )r   aranger-   int64rU   stackr   r*   r+   r   r   signlog2absr   tonextr   
parametersr<   r~   sum)
rL   relative_coords_hrelative_coords_wr   coords_hcoords_wcoordscoords_flattenrelative_coordsr   s
             r!   r   z2Swin2SRSelfAttention.create_coords_table_and_indexH  s7   !LL4+;+;A+>+B)CTEUEUVWEX`e`k`klrrt!LL4+;+;A+>+B)CTEUEUVWEX`e`k`klrrtKK"35F!GRVWXWQ1Z\Yq\	 	 &&q)A-!!Q1*-1L1LQ1ORS1SS-!!Q1*-1L1LQ1ORS1SS-a 1$!!Q1*-1A1A!1Dq1HH-!!Q1*-1A1A!1Dq1HH-"JJ,-

599EZ;[^a;a0bbeienenopeqq 	 !6 8 8d>_>_>j>j>l9m9s9s t << 0 0 34<< 0 0 34Xx&:TJKvq1(At4~aqj7QQ)11!Q:EEG1a D$4$4Q$7!$;; 1a D$4$4Q$7!$;; 1a A(8(8(;$;a$?? "1"5"5b"9$&===r    NF)r   r   r   rK   r   rV   r   boolr   rP   r   rX   rY   s   @r!   r   r      sm    TUWXSY G@ 48).	B||B ))D0B  $;	B
 
u||	BH#>r    r   c                   n     e Zd Z fdZdej
                  dej
                  dej
                  fdZ xZS )Swin2SRSelfOutputc                     t         |           t        j                  ||      | _        t        j
                  |j                        | _        y rI   )rJ   rK   r   r   densere   r   rg   rL   rh   r   rM   s      r!   rK   zSwin2SRSelfOutput.__init__p  s6    YYsC(
zz&"E"EFr    r   input_tensorr9   c                 J    | j                  |      }| j                  |      }|S rI   r   rg   )rL   r   r   s      r!   rP   zSwin2SRSelfOutput.forwardu  s$    

=1]3r    r   r   r   rK   r   rV   rP   rX   rY   s   @r!   r   r   o  s2    G
U\\  RWR^R^ r    r   c            
            e Zd Zd fd	Z	 	 d	dej
                  dej                  dz  dedz  deej
                     fdZ	 xZ
S )
Swin2SRAttentionc           
          t         |           t        ||||t        |t        j
                  j                        r|n||f      | _        t        ||      | _	        y )Nrh   r   r   r-   r   )
rJ   rK   r   rs   rt   ru   rv   rL   r   rD   )rL   rh   r   r   r-   r   rM   s         r!   rK   zSwin2SRAttention.__init__~  sY    (#0+//2J2JK $:(*@A
	 (4r    Nr   r   r   r9   c                 h    | j                  |||      }| j                  |d   |      }|f|dd  z   }|S Nr   r   )rL   rD   )rL   r   r   r   self_outputsattention_outputr   s          r!   rP   zSwin2SRAttention.forward  sE     yy@QR;;|AF#%QR(88r    r   r   )r   r   r   rK   r   rV   r   r   r   rP   rX   rY   s   @r!   r   r   }  sW    5  48).		||	 ))D0	  $;		
 
u||		r    r   c                   V     e Zd Z fdZdej
                  dej
                  fdZ xZS )Swin2SRIntermediatec                    t         |           t        j                  |t	        |j
                  |z              | _        t        |j                  t              rt        |j                     | _        y |j                  | _        y rI   )rJ   rK   r   r   r   	mlp_ratior   rs   
hidden_actrW   r   intermediate_act_fnr   s      r!   rK   zSwin2SRIntermediate.__init__  sa    YYsC(8(83(>$?@
f''-'-f.?.?'@D$'-'8'8D$r    r   r9   c                 J    | j                  |      }| j                  |      }|S rI   )r   r	  rO   s     r!   rP   zSwin2SRIntermediate.forward  s&    

=100?r    r   rY   s   @r!   r  r    s#    9U\\ ell r    r  c                   V     e Zd Z fdZdej
                  dej
                  fdZ xZS )Swin2SROutputc                     t         |           t        j                  t	        |j
                  |z        |      | _        t        j                  |j                        | _	        y rI   )
rJ   rK   r   r   r   r  r   re   rf   rg   r   s      r!   rK   zSwin2SROutput.__init__  sF    YYs6#3#3c#9:C@
zz&"<"<=r    r   r9   c                 J    | j                  |      }| j                  |      }|S rI   r   rO   s     r!   rP   zSwin2SROutput.forward  s$    

=1]3r    r   rY   s   @r!   r  r    s#    >
U\\ ell r    r  c                        e Zd Z	 d fd	Zdeeeef   eeef   f   fdZd Zd Z	 dde	j                  deeef   ded	z  dee	j                  e	j                  f   fd
Z xZS )Swin2SRLayerc           
      n   t         	|           || _        | j                  |j                  |j                  f||f      \  }}|d   | _        |d   | _        t        |||| j                  t        |t        j                  j                        r|n||f      | _        t        j                  ||j                        | _        |dkD  rt!        |      nt        j"                         | _        t'        ||      | _        t+        ||      | _        t        j                  ||j                        | _        y )Nr   r   epsr;   )rJ   rK   r   _compute_window_shiftr-   
shift_sizer   rs   rt   ru   rv   	attentionr   rz   layer_norm_epslayernorm_beforerG   IdentityrE   r  intermediater  rD   layernorm_after)
rL   rh   r   r   r   drop_path_rater  r   r-   rM   s
            r!   rK   zSwin2SRLayer.__init__  s    	 0"&"<"<!3!34z:6N#
Z 'q>$Q-)((0+//2J2JK $:(*@A
 !#Sf6K6K L<JS<P8VXVaVaVc/<#FC0!||CV5J5JKr    r9   c                     t        | j                  |      D cg c]  \  }}t        ||       }}}t        | j                  ||      D cg c]  \  }}}||k  rdn| }}}}||fS c c}}w c c}}}w Nr   )zipr   min)rL   target_window_sizetarget_shift_sizerwr-   sr  s           r!   r  z"Swin2SRLayer._compute_window_shift  sy    -01F1FHZ-[\TQs1ay\\8;D<Q<QS^`q8rssWQ116aq(s
sJ&& ]ss   A*A0c           	         | j                   dkD  rgt        j                  d||df|      }t        d| j                         t        | j                   | j                          t        | j                    d       f}t        d| j                         t        | j                   | j                          t        | j                    d       f}d}|D ]  }|D ]  }	||d d ||	d d f<   |dz  }  t        || j                        }
|
j                  d| j                  | j                  z        }
|
j                  d      |
j                  d      z
  }|j                  |dk7  d      j                  |dk(  d      }|S d }|S )Nr   r   r   r&   r#   g      Yr;   )	r  r   rb   slicer-   r3   r)   r   masked_fill)rL   r/   r0   r<   img_maskheight_sliceswidth_slicescountheight_slicewidth_slicemask_windows	attn_masks               r!   get_attn_maskzSwin2SRLayer.get_attn_mask  s   ??Q{{Avua#8FHa$***+t'''$//)9:t&-M a$***+t'''$//)9:t&-L
 E - #/ K@EHQk1<=QJE
 ,Hd6F6FGL',,R1A1ADDTDT1TUL$..q1L4J4J14MMI!--i1nfEQQR[_`R`befI  Ir    c                     | j                   || j                   z  z
  | j                   z  }| j                   || j                   z  z
  | j                   z  }ddd|d|f}t        j                  j                  ||      }||fS r  )r-   r   r   r   )rL   r   r/   r0   	pad_right
pad_bottomr   s          r!   r   zSwin2SRLayer.maybe_pad  s    %%0@0@(@@DDTDTT	&&$2B2B)BBdFVFVV
Ay!Z8
))-Dj((r    r   r   r   Nc                    |\  }}|j                         \  }}}|}	|j                  ||||      }| j                  |||      \  }}
|j                  \  }}}}| j                  dkD  r1t        j                  || j                   | j                   fd      }n|}t        || j                        }|j                  d| j                  | j                  z  |      }| j                  |||j                        }||j                  |j                        }| j                  |||      }|d   }|j                  d| j                  | j                  |      }t        || j                  ||      }| j                  dkD  r/t        j                  || j                  | j                  fd      }n|}|
d   dkD  xs |
d   dkD  }|r|d d d |d |d d f   j                         }|j                  |||z  |      }| j!                  |      }|	| j#                  |      z   }| j%                  |      }| j'                  |      }|| j#                  | j)                  |            z   }|r	||d	   f}|S |f}|S )
Nr   )r   r#   )shiftsdimsr&   r   )r   r   r%   r   )r   r)   r   r(   r  r   rollr3   r-   r1  r<   r   r=   r  r5   r+   r  rE   r  rD   r  )rL   r   r   r   r/   r0   r.   r   channelsshortcutr   
height_pad	width_padshifted_hidden_stateshidden_states_windowsr0  attention_outputsr  attention_windowsshifted_windows
was_paddedlayer_outputlayer_outputss                          r!   rP   zSwin2SRLayer.forward  s    )"/"4"4"6
Ax  &**:vuhO$(NN=&%$P!z&3&9&9#:y!??Q$)JJ}tFVY]YhYhXhEipv$w!$1! !11FHXHX Y 5 : :2t?O?ORVRbRb?bdl m&&z9MDWDW&X	 !%:%A%ABI NN+@)_pNq,Q/,11"d6F6FHXHXZbc():D<L<LjZcd ??Q %

?DOOUYUdUdCelr s /]Q&;*Q-!*;
 1!WfWfufa2G H S S U-22:v~xX--.?@ 4>>-#@@((7{{<0$t~~d6J6J<6X'YY@Q'8';< YeWfr    )r;   r   r   F)r   r   r   rK   r   r   r  r1  r   r   rV   r   rP   rX   rY   s   @r!   r  r    s    qrL2'eTYZ]_bZbTcejknpsksetTtNu '
8) */	5||5  S/5  $;	5
 
u||U\\)	*5r    r  c            
       ~     e Zd ZdZd	 fd	Z	 d
dej                  deeef   de	dz  deej                     fdZ
 xZS )Swin2SRStagezh
    This corresponds to the Residual Swin Transformer Block (RSTB) in the original implementation.
    c                    t         	|           || _        || _        t	        j
                  t        |      D cg c]*  }t        |||||dz  dk(  rdn|j                  dz  |      , c}      | _	        |j                  dk(  rt	        j                  ||ddd      | _        n|j                  dk(  rt	        j                  t	        j                  ||dz  ddd      t	        j                  d	d
      t	        j                  |dz  |dz  ddd      t	        j                  d	d
      t	        j                  |dz  |ddd            | _        t        |d      | _        t#        |      | _        y c c}w )Nr#   r   )rh   r   r   r   r  r   1convr   r   3convr$   皙?Tnegative_sloper   F)r|   )rJ   rK   rh   r   r   
ModuleListranger  r-   layersresi_connectionrx   convr   	LeakyReLUr]   patch_embedr   patch_unembed)
rL   rh   r   r   depthr   rE   r   irM   s
            r!   rK   zSwin2SRStage.__init__4  sI   mm u
  !%5'%&UaZqf6H6HA6M+A

 !!W,		#sAq!4DI##w.		#saxAq1C>		#(C1HaA6C>		#(CAq1DI 2&ER5f=7
s   /E.r   r   r   Nr9   c                    |}|\  }}t        | j                        D ]  \  }} ||||      }	|	d   } ||||f}
| j                  ||      }| j                  |      }| j	                  |      \  }}||z   }||
f}|r|	dd  z  }|S r   )	enumeraterP  rU  rR  rT  )rL   r   r   r   residualr/   r0   rW  layer_modulerD  rl   r   stage_outputss                r!   rP   zSwin2SRStage.forwardV  s     !((5 	-OA|(8HJ[\M)!,M	-
 $UFE:**=:JK		-0++M:q%0&(9:]12..Mr    r  rE  )r   r   r   rT   rK   r   rV   r   r   r   rP   rX   rY   s   @r!   rG  rG  /  sW     >L */	||  S/  $;	
 
u||	r    rG  c                   |     e Zd Z fdZ	 	 	 d
dej
                  deeef   dedz  dedz  dedz  dee	z  fd	Z
 xZS )Swin2SREncoderc                 z   t         |           t        |j                        | _        || _        t        j                  d|j                  t        |j                        d      D cg c]  }|j                          }}t        j                  t        | j                        D cg c]r  }t        ||j                  |d   |d   f|j                  |   |j                   |   |t        |j                  d |       t        |j                  d |dz           d      t c}      | _        d| _        y c c}w c c}w )Nr   cpu)r=   r   )rh   r   r   rV  r   rE   r   F)rJ   rK   lendepths
num_stagesrh   r   linspacer  r   itemr   rN  rO  rG  rc   r   stagesgradient_checkpointing)rL   rh   	grid_sizexdpr	stage_idxrM   s         r!   rK   zSwin2SREncoder.__init__t  s   fmm,!&63H3H#fmmJ\ej!klAqvvxllmm "'t!7  !((&/lIaL%A --	2$..y9!#fmmJY&?"@3v}}UdW`cdWdGeCfg+,
 ',#! ms   )D3(A7D8r   r   r   Noutput_hidden_statesreturn_dictr9   c                     d}|rdnd }|rdnd }|r||fz  }t        | j                        D ]<  \  }	}
 |
|||      }|d   }|d   }|d   |d   f}||fz  }|r||fz  }|s5||dd  z  }> |st        d |||fD              S t        |||      S )	Nr   r   r   r   r&   r#   c              3   &   K   | ]	  }||  y wrI   r   ).0vs     r!   	<genexpr>z)Swin2SREncoder.forward.<locals>.<genexpr>  s     mq_`_lms   r   r   r   )rY  rf  r   r   )rL   r   r   r   rl  rm  all_input_dimensionsall_hidden_statesall_self_attentionsrW  stage_modulerD  rl   s                r!   rP   zSwin2SREncoder.forward  s      ""6BD$5b4-!11(5 	9OA|(8HJ[\M)!,M -a 0 1" 57H7LM %5$77 #!m%55! #}QR'88#	9 m]4EGZ$[mmm#++*
 	
r    )FFT)r   r   r   rK   r   rV   r   r   r   r   rP   rX   rY   s   @r!   r^  r^  s  sp    ,4 */,1#'%
||%
  S/%
  $;	%

 #Tk%
 D[%
 
%	%%
r    r^  c                   V    e Zd ZU eed<   dZdZdZdZ e	j                         d        Zy)Swin2SRPreTrainedModelrh   swin2srri   )imageTc                 F   t        |t        j                  t        j                  f      rbt	        j
                  |j                  | j                  j                         |j                   t	        j                  |j                         yyt        |t        j                        r?t	        j                  |j                         t	        j                  |j                         yt        |t              rt	        j                  |j                  t!        j"                  d             |j%                         \  }}t	        j&                  |j(                  |       t	        j&                  |j*                  |       yt        |t,              r|j                  j.                  dk(  rC|j                  j0                  dk(  r*t3        j4                  g d      j7                  dddd      }nt3        j8                  dddd      }t	        j&                  |j:                  |       yy)zInitialize the weights)stdNr   r   gw#?g8EGr?gB`"?r   )rs   r   r   rx   inittrunc_normal_weightrh   initializer_ranger   zeros_rz   ones_r   	constant_r   r   r   r   copy_r   r   Swin2SRModelr1   num_channels_outr   tensorr)   rb   mean)rL   moduler   r   r  s        r!   _init_weightsz$Swin2SRPreTrainedModel._init_weights  se    fryy"))45v}}$++2O2OP{{&FKK( '-KK$JJv}}% 45NN6--txx|<=C=a=a=c:!#:JJv335JKJJv557NO-}}))Q.6==3Q3QUV3V||$<=BB1aAN{{1aA.JJv{{D) .r    N)r   r   r   r   r   base_model_prefixmain_input_nameinput_modalitiessupports_gradient_checkpointingr   no_gradr  r   r    r!   ry  ry    s9    !$O!&*#U]]_* *r    ry  c                        e Zd Z fdZd Zd Ze	 	 	 ddej                  de	dz  de	dz  de	dz  d	e
ez  f
d
       Z xZS )r  c                 $   t         |   |       || _        |j                  dk(  r9|j                  dk(  r*t        j                  g d      j                  dddd      }nt        j                  dddd      }| j                  d|d       |j                  | _
        t        j                  |j                  |j                  ddd      | _        t        |      | _        t#        || j                   j$                  j&                        | _        t        j*                  |j                  |j,                        | _        t1        |      | _        t        j                  |j                  |j                  ddd      | _        | j7                          y )	Nr   r~  r   r  Fr   )rh  r  )rJ   rK   rh   r1   r  r   r  r)   rb   r   	img_ranger   rx   rc   first_convolutionr[   rk   r^  r^   rw   encoderrz   r  r{   r   rU  conv_after_body	post_init)rL   rh   r  rM   s      r!   rK   zSwin2SRModel.__init__  s8    !#(?(?1(D<< 89>>q!QJD;;q!Q*DVTe<))!#6+>+>@P@PRSUVXY!Z+F3%f8X8X8k8klf&6&6F<Q<QR5f=!yy)9)96;K;KQPQSTU 	r    c                 .    | j                   j                  S rI   )rk   r^   rR   s    r!   get_input_embeddingsz!Swin2SRModel.get_input_embeddings  s    ///r    c                 ,   |j                         \  }}}}| j                  j                  }|||z  z
  |z  }|||z  z
  |z  }t        j                  j                  |d|d|fd      }| j                  j                  |      }||z
  | j                  z  }|S )Nr   reflect)	r   rh   r-   r   r   r   r  type_asr  )	rL   ri   r   r/   r0   r-   modulo_pad_heightmodulo_pad_widthr  s	            r!   pad_and_normalizezSwin2SRModel.pad_and_normalize  s    *//11fe kk--(6K+??;N'%+*==L}}((;KQPa7bdmn yy  .$t+t~~=r    Nri   r   rl  rm  r9   c                 2   ||n| j                   j                  }||n| j                   j                  }||n| j                   j                  }|j                  \  }}}}| j                  |      }| j                  |      }	| j                  |	      \  }
}| j                  |
||||      }|d   }| j                  |      }| j                  |||f      }| j                  |      |	z   }|s|f|dd  z   }|S t        ||j                  |j                        S )Nr   rl  rm  r   r   rs  )rh   r   rl  use_return_dictr(   r  r  rk   r  r{   rU  r  r	   r   r   )rL   ri   r   rl  rm  kwargsr   r/   r0   rk   embedding_outputr   encoder_outputssequence_outputrD   s                  r!   rP   zSwin2SRModel.forward  sB    2C1N-TXT_T_TqTq$8$D $++JjJj 	 &1%<k$++B]B]*001fe --l;++L9
-1__Z-H**,,/!5# ' 
 *!,..9,,_vuoN..?*L%'/!"*==FM-)77&11
 	
r    )NNN)r   r   r   rK   r  r  r   r   r   r   r   r	   rP   rX   rY   s   @r!   r  r    sx    .0  *.,0#'-
''-
  $;-
 #Tk	-

 D[-
 
	 -
 -
r    r  c                   (     e Zd ZdZ fdZd Z xZS )UpsamplezUpsample module.

    Args:
        scale (`int`):
            Scale factor. Supported scales: 2^n and 3.
        num_features (`int`):
            Channel number of intermediate features.
    c                    t         |           || _        ||dz
  z  dk(  rt        t	        t        j                  |                  D ]Y  }| j                  d| t        j                  |d|z  ddd             | j                  d| t        j                  d             [ y |dk(  r<t        j                  |d|z  ddd      | _        t        j                  d      | _        y t        d	| d
      )Nr   r   convolution_r$   r   pixelshuffle_r#   	   zScale z/ is not supported. Supported scales: 2^n and 3.)rJ   rK   scalerO  r   r   r   
add_moduler   rx   PixelShuffleconvolutionpixelshuffler   )rL   r  num_featuresrW  rM   s       r!   rK   zUpsample.__init__7  s    
UQYA%3tyy/01 I,qc 2BIIlAP\L\^_abde4fg-s 3R__Q5GHI aZ!yyq<7GAqQD " 2DveW,[\]]r    c                 ~   | j                   | j                   dz
  z  dk(  rlt        t        t        j                  | j                                     D ]6  } | j                  d|       |      } | j                  d|       |      }8 |S | j                   dk(  r"| j                  |      }| j                  |      }|S )Nr   r   r  r  r   )r  rO  r   r   r   __getattr__r  r  )rL   hidden_staterW  s      r!   rP   zUpsample.forwardF  s    JJ$**q.)a/3tyy456 SCt//,qc0BCLQDt//-s0CD\RS 	 ZZ1_++L9L,,\:Lr    r   rY   s   @r!   r  r  -  s    ^
r    r  c                   (     e Zd ZdZ fdZd Z xZS )UpsampleOneStepa  UpsampleOneStep module (the difference with Upsample is that it always only has 1conv + 1pixelshuffle)

    Used in lightweight SR to save parameters.

    Args:
        scale (int):
            Scale factor. Supported scales: 2^n and 3.
        in_channels (int):
            Channel number of intermediate features.
        out_channels (int):
            Channel number of output features.
    c                     t         |           t        j                  ||dz  |z  ddd      | _        t        j
                  |      | _        y )Nr#   r   r   )rJ   rK   r   rx   rR  r  pixel_shuffle)rL   r  in_channelsout_channelsrM   s       r!   rK   zUpsampleOneStep.__init__a  s@    IIkE1H+DaAN	__U3r    c                 J    | j                  |      }| j                  |      }|S rI   )rR  r  )rL   ri  s     r!   rP   zUpsampleOneStep.forwardg  s$    IIaLq!r    r   rY   s   @r!   r  r  S  s    4r    r  c                   $     e Zd Z fdZd Z xZS )PixelShuffleUpsamplerc                 .   t         |           t        j                  |j                  |ddd      | _        t        j                  d      | _        t        |j                  |      | _
        t        j                  ||j                  ddd      | _        y Nr   r   Tr   )rJ   rK   r   rx   rc   conv_before_upsamplerS  
activationr  upscaleupsampler  final_convolutionrL   rh   r  rM   s      r!   rK   zPixelShuffleUpsampler.__init__o  ss    $&IIf.>.>aQRTU$V!,,t4 >!#<9P9PRSUVXY!Zr    c                     | j                  |      }| j                  |      }| j                  |      }| j                  |      }|S rI   )r  r  r  r  )rL   r  ri  s      r!   rP   zPixelShuffleUpsampler.forwardv  sC    %%o6OOAMM!""1%r    r   r   r   rK   rP   rX   rY   s   @r!   r  r  n  s    [r    r  c                   $     e Zd Z fdZd Z xZS )NearestConvUpsamplerc                    t         |           |j                  dk7  rt        d      t	        j
                  |j                  |ddd      | _        t	        j                  d      | _	        t	        j
                  ||ddd      | _
        t	        j
                  ||ddd      | _        t	        j
                  ||ddd      | _        t	        j
                  ||j                  ddd      | _        t	        j                  dd      | _        y )	Nr$   zNThe nearest+conv upsampler only supports an upscale factor of 4 at the moment.r   r   Tr   rK  rL  )rJ   rK   r  r   r   rx   rc   r  rS  r  conv_up1conv_up2conv_hrr  r  lrelur  s      r!   rK   zNearestConvUpsampler.__init__  s    >>Qmnn$&IIf.>.>aQRTU$V!,,t4		,aAF		,aAFyy|Q1E!#<9P9PRSUVXY!Z\\dC
r    c           	         | j                  |      }| j                  |      }| j                  | j                  t        j
                  j                  j                  |dd                  }| j                  | j                  t        j
                  j                  j                  |dd                  }| j                  | j                  | j                  |                  }|S )Nr#   nearest)scale_factormode)r  r  r  r  r   r   r   interpolater  r  r  )rL   r  reconstructions      r!   rP   zNearestConvUpsampler.forward  s    33OD///:**MM%((--99/XY`i9jk
 **MM%((--99/XY`i9jk
 //

4<<;X0YZr    r  rY   s   @r!   r  r    s    D
r    r  c                   $     e Zd Z fdZd Z xZS )PixelShuffleAuxUpsamplerc           	      |   t         |           |j                  | _        t        j                  |j
                  |ddd      | _        t        j                  |j                  |ddd      | _        t        j                  d      | _
        t        j                  ||j
                  ddd      | _        t        j                  t        j                  d|ddd      t        j                  d            | _        t        |j                  |      | _        t        j                  ||j                   ddd      | _        y r  )rJ   rK   r  r   rx   r1   conv_bicubicrc   r  rS  r  conv_auxr   conv_after_auxr  r  r  r  r  s      r!   rK   z!PixelShuffleAuxUpsampler.__init__  s    ~~IIf&9&9<AqQ$&IIf.>.>aQRTU$V!,,t4		,0C0CQ1M mmBIIaq!Q,OQSQ]Q]fjQkl >!#<9P9PRSUVXY!Zr    c                    | j                  |      }| j                  |      }| j                  |      }| j                  |      }| j	                  |      }| j                  |      d d d d d || j                  z  d || j                  z  f   |d d d d d || j                  z  d || j                  z  f   z   }| j                  |      }||fS rI   )r  r  r  r  r  r  r  r  )rL   r  bicubicr/   r0   auxr  s          r!   rP   z PixelShuffleAuxUpsampler.forward  s    ##G,33OD///:mmO,--c2MM/*1a1H6DLL3H1HJ`ETXT`T`L`J`+`aa3ft||335Kut||7K5KKLM 	 //@s""r    r  rY   s   @r!   r  r    s    
[#r    r  zm
    Swin2SR Model transformer with an upsampler head on top for image super resolution and restoration.
    c                        e Zd Z fdZe	 	 	 	 	 d
dej                  dz  dej                  dz  dedz  dedz  dedz  de	e
z  fd	       Z xZS )Swin2SRForImageSuperResolutionc                 V   t         |   |       t        |      | _        |j                  | _        |j
                  | _        d}| j                  dk(  rt        ||      | _        n| j                  dk(  rt        ||      | _        n| j                  dk(  r1t        |j
                  |j                  |j                        | _        nS| j                  dk(  rt        ||      | _        n2t        j                  |j                  |j                  ddd      | _        | j!                          y )N@   r  pixelshuffle_auxpixelshuffledirectnearest+convr   r   )rJ   rK   r  rz  	upsamplerr  r  r  r  r  rc   r  r  r   rx   r  r  r  s      r!   rK   z'Swin2SRForImageSuperResolution.__init__  s     #F+))~~ >>^+1&,GDM^^114V\JDM^^33+FNNF<L<LfNeNefDM^^~-0FDM &(YYv/?/?AXAXZ[]^`a%bD" 	r    Nri   labelsr   rl  rm  r9   c                    ||n| j                   j                  }d}|t        d      |j                  dd \  }}	| j                   j                  dk(  r?t
        j                  j                  ||| j                  z  |	| j                  z  fdd      }
| j                  ||||      }|d	   }| j                  d
v r| j                  |      }nk| j                  dk(  rH| j                  |
||	      \  }}|| j                  j                  z  | j                  j                  z   }n|| j                  |      z   }|| j                  j                  z  | j                  j                  z   }|ddddd|| j                  z  d|	| j                  z  f   }|s|f|dd z   }||f|z   S |S t        |||j                  |j                         S )a  
        Example:
         ```python
         >>> import torch
         >>> import numpy as np
         >>> from PIL import Image
         >>> import httpx
        >>> from io import BytesIO

         >>> from transformers import AutoImageProcessor, Swin2SRForImageSuperResolution

         >>> processor = AutoImageProcessor.from_pretrained("caidas/swin2SR-classical-sr-x2-64")
         >>> model = Swin2SRForImageSuperResolution.from_pretrained("caidas/swin2SR-classical-sr-x2-64")

         >>> url = "https://huggingface.co/spaces/jjourney1125/swin2sr/resolve/main/samples/butterfly.jpg"
         >>> with httpx.stream("GET", url) as response:
         ...     image = Image.open(BytesIO(response.read()))
         >>> # prepare image for the model
         >>> inputs = processor(image, return_tensors="pt")

         >>> # forward pass
         >>> with torch.no_grad():
         ...     outputs = model(**inputs)

         >>> output = outputs.reconstruction.data.squeeze().float().cpu().clamp_(0, 1).numpy()
         >>> output = np.moveaxis(output, source=0, destination=-1)
         >>> output = (output * 255.0).round().astype(np.uint8)  # float32 to uint8
         >>> # you can visualize `output` with `Image.fromarray`
         ```Nz'Training is not supported at the momentr#   r  r  F)r   r  align_cornersr  r   )r  r  r  r   )lossr  r   r   )rh   r  NotImplementedErrorr(   r  r   r   r  r  rz  r  r  r  r  r
   r   r   )rL   ri   r  r   rl  rm  r  r  r/   r0   r  r   r  r  r  rD   s                   r!   rP   z&Swin2SRForImageSuperResolution.forward  s   N &1%<k$++B]B]%&OPP$**12.;;  $66mm//t||+UT\\-AB#	 0 G ,,/!5#	  
 "!*>>SS!]]?;N^^11"&--&RW"XNC...1B1BBC)D,B,B?,SSN'$,,*@*@@4<<CTCTT'1.E0E.EG]QUQ]Q]I]G](]^$&4F)-)9TGf$EvE))!//))	
 	
r    )NNNNN)r   r   r   rK   r   r   r   
LongTensorr   r   r
   rP   rX   rY   s   @r!   r  r    s    4  26*.)-,0#'S
''$.S
   4'S
  $;	S

 #TkS
 D[S
 
+	+S
 S
r    r  )r  r  ry  )r;   F)=rT   collections.abcrt   r   dataclassesr   r   r    r   r  activationsr   modeling_layersr   modeling_outputsr	   r
   modeling_utilsr   pytorch_utilsr   utilsr   r   r   configuration_swin2srr   
get_loggerr   loggerr   r3   r5   rV   rU   r   rE   r   rG   r[   r]   r   r   r   r   r   r  r  r  rG  r^  ry  r  r  r  r  r  r  r  __all__r   r    r!   <module>r     sA   )   !   & ! 9 K - % 9 9 0 
		H	% 
7; 7 7	U\\ e T V[VbVb  %bii %-		 -<-RYY -6ryy 3")) 3nE>299 E>R
		 
ryy 6"))  	BII 	w299 wtA- AH<
RYY <
~ *_ * *< X
) X
 X
v#ryy #Lbii 6BII "299 6#ryy #8 
o
%; o

o
d Wr    