U
    *-e!.                     @   sX   d dl Z d dlmZ d dlmZ G dd deZG dd deZG dd de jjZ	dS )	    N)Functionc                   @   s$   e Zd Zedd Zedd ZdS )SyncBatchNormc
              
      sr  |j tjds$|j tjds$| }|d k	r4| }t| |d }
|
dkrh|	dk rhtd|
 |j	d }| dkrt
||\}}tjd| |d |j|jd}tj|||gdd ntjd| d |j|jd | d	krN  }tjd||	  j jd}tj| |d
d t||	|f tj |dd\}}}nL fddt|	D }tj| |d
d tj|dd tj |dd\}}}tj rtj s|ddk}|| }|| }|| }|d}|d k	r|j|jkr||j}t||||||||\}}|  |||||tj! || _"| dkrdt#||||||S t$|S d S )NZmemory_format      zEExpected more than 1 value per channel when training, got input size r   )r   dtypedevicedimZglooFZasync_opc                    s   g | ]}t  qS  )torch
empty_like).0_combinedr   \/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/torch/nn/modules/_functions.py
<listcomp>B   s    z)SyncBatchNorm.forward.<locals>.<listcomp>)%is_contiguousr   channels_lastchannels_last_3d
contiguousintnumelsize
ValueErrorshapeZbatch_norm_statsfullr   r	   catzerosZ_get_backend_nameemptydistZall_gather_into_tensorZreshapesplitrangeZ
all_gatherstackcudaZis_availableZis_current_stream_capturingZsqueezeviewtoZ#batch_norm_gather_stats_with_countssave_for_backwardZint32process_groupZbatch_norm_elemtr   )selfinputweightZbiasZrunning_meanZrunning_varZepsZmomentumr,   Z
world_sizer   num_channelsmeaninvstdcountZcombined_sizeZcombined_flatZmean_allZ
invstd_allZ	count_allZcombined_listmaskcountsr   r   r   forward   s    


	
zSyncBatchNorm.forwardc                 C   s  |j tjds$|j tjds$| }| j\}}}}}d  } }}	| j}
| dkrFt|||||| j	d | j	d | j	d \}}}}	| j	d r|j
d }tj||gdd}tjj|tjjj|
dd t||\}}|d k	r|j|jkr||j}t||||||||}|d ks&| j	d s*d }|d ks@| j	d sd }	nH|j
d }| j	d rtjd| |j|jd}tjj|tjjj|
dd |||	d d d d d d f	S )	Nr   r   r   r   r
   Fr   r   )r   r   r   r   r   saved_tensorsr,   r   Zbatch_norm_backward_reduceZneeds_input_gradr   r!   distributedZ
all_reduceZReduceOpZSUMr%   r   r*   Zbatch_norm_backward_elemtr"   r	   )r-   grad_outputZsaved_inputr/   r1   r2   Zcount_tensor
grad_inputZgrad_weightZ	grad_biasr,   Zsum_dyZ
sum_dy_xmur0   r   r   r   r   backwardp   sv    
   
   zSyncBatchNorm.backwardN__name__
__module____qualname__staticmethodr6   r;   r   r   r   r   r      s   
gr   c                   @   s&   e Zd Zed	ddZedd ZdS )
CrossMapLRN2d-C6?      ?r   c                 C   s  || _ || _|| _|| _d | _| dkr>td|  d| jpJ| | _| }| d}| d}| d}	| d}
|| | j| |}t	j
|d|d t| j d d d }||kr|n|}| jdd}|  t|D ]}||d| qtd|D ]}| jd|d }| jd|}|| ||| d k rp|d|| d }|j|dd	 ||kr|d|| }|j|d
d	 q| j| j| j  | j t	j
| j| j |d || | || |S )N   z,CrossMapLRN2d: Expected input to be 4D, got z
D instead.r   r   r      outalphar   )r   rI   betakscaler   r   new
resize_as_r   powr   selectzero_r&   add_Zcopy_mul_r+   )ctxr.   r   rI   rJ   rK   output
batch_sizechannelsinput_heightinput_widthZinput_squareZpre_padZpre_pad_cropZscale_firstcZscale_previousZscale_currentZsquare_nextZsquare_previousr   r   r   r6      sL    







zCrossMapLRN2d.forwardc                 C   s  | j \}}| }|d}|d}|d}|d}||| j d ||}	|||}
d| j | j | j }t| j| jd d  }|| tj| j	| j |d
| |	  |	d||}t|D ]}tj|| || |d || j	|  tj|	dd| jd dd|
d t|D ]R}|
|	|| j d   || | j|| | |
| d |
j|	| d	d
 q&q|d d d d fS )Nr   r   r   rE   rF   F)ZkeepdimrG   )valuer   rH   )r7   rM   r   rI   rJ   r   rN   r   rO   rL   rS   rQ   Znarrowr&   mulZdiv_sumrR   Zaddcmul_)rT   r9   r.   rU   r:   rV   rW   rX   rY   Zpaddded_ratioZaccum_ratioZcache_ratio_valueZinversePrePadZpadded_ratio_centernrZ   r   r   r   r;      s@    





   "zCrossMapLRN2d.backwardN)rB   rC   r   r<   r   r   r   r   rA      s   8rA   c                   @   s$   e Zd Zedd Zedd ZdS )BackwardHookFunctionc                 G   s   | j dd |D   |S )Nc                 S   s   g | ]}|j s|qS r   )Zrequires_grad)r   argr   r   r   r     s      z0BackwardHookFunction.forward.<locals>.<listcomp>)Zmark_non_differentiablerT   argsr   r   r   r6     s    zBackwardHookFunction.forwardc                 G   s   |S )Nr   ra   r   r   r   r;     s    zBackwardHookFunction.backwardNr<   r   r   r   r   r_     s   
r_   )
r   Ztorch.distributedr8   r$   Ztorch.autograd.functionr   r   rA   Zautogradr_   r   r   r   r   <module>   s    5^