Ph .ddlZddlmZddlZgdZdZGddZGddZGd d ZGd d Z ejjjejjjejjjd Zdj!ej#Z d#dedeejjfdejjfdZddlmZmZde_de_dZdefdZdZdefdZdZ defdZ!d$dededefdZ"d$dededefdZ#ejH d%ded ed!efd"Z%eZ&e Z'y)&N)Union)is_builtcuFFTPlanCacheAttrContextPropcuFFTPlanCachecuFFTPlanCacheManager cuBLASModulepreferred_linalg_librarycufft_plan_cachematmul SDPBackend SDPAParamsenable_flash_sdpflash_sdp_enabledenable_mem_efficient_sdpmem_efficient_sdp_enabledmath_sdp_enabledenable_math_sdpcan_use_flash_attentioncan_use_efficient_attention sdp_kernelc6tjjS)z Return whether PyTorch is built with CUDA support. Note that this doesn't necessarily mean CUDA is available; just that if this PyTorch binary were run on a machine with working CUDA drivers and devices, we would be able to use it. )torch_C _has_cudagC:\Users\daisl\Desktop\realtime-object-detection\venv\Lib\site-packages\torch/backends/cuda/__init__.pyrrs 88  rceZdZdZdZdZy)rc ||_||_yN)gettersetter)selfr!r"s r__init__z&cuFFTPlanCacheAttrContextProp.__init__+s  rc8|j|jSr )r! device_index)r#objobjtypes r__get__z%cuFFTPlanCacheAttrContextProp.__get__/s{{3++,,rct|jtrt|j|j|j|yr ) isinstancer"str RuntimeErrorr&)r#r'vals r__set__z%cuFFTPlanCacheAttrContextProp.__set__2s3 dkk3 't{{+ + C$$c*rN)__name__ __module__ __qualname__r$r)r/rrrrr(s-+rrc|eZdZdZdZeejdZeejejZ dZ y)rz Represent a specific plan cache for a specific `device_index`. The attributes `size` and `max_size`, and method `clear`, can fetch and/ or change properties of the C++ cuFFT plan cache. c||_yr )r&)r#r&s rr$zcuFFTPlanCache.__init__@s (rz.size is a read-only property showing the number of plans currently in the cache. To change the cache capacity, set cufft_plan_cache.max_size.c@tj|jSr )r_cufft_clear_plan_cacher&r#s rclearzcuFFTPlanCache.clearMs,,T->->??rN) r0r1r2__doc__r$rr_cufft_get_plan_cache_sizesize_cufft_get_plan_cache_max_size_cufft_set_plan_cache_max_sizemax_sizer8rrrrr8sJ) ) (( N D - ,,e.R.RH@rrc8eZdZdZdZdZdZdZfdZxZ S)ra Represent all cuFFT plan caches, return the cuFFTPlanCache for a given device when indexed. Finally, this object, when used directly as a `cuFFTPlanCache` object (e.g., setting the `.max_size`) attribute, the current device's cuFFT plan cache is used. Fc g|_d|_y)NT)caches#_cuFFTPlanCacheManager__initializedr7s rr$zcuFFTPlanCacheManager.__init__\s !rctjjj|}|dks!|tjj k\r-t dtjj d|t |jdk(rG|jjdttjj D|j|S)Nrz/cufft_plan_cache: expected 0 <= device index < z, but got device with index c32K|]}t|ywr )r).0indexs r z4cuFFTPlanCacheManager.__getitem__..hs3S%u%3Ss) rcuda_utils_get_device_index device_countr-lenrAextendrange)r#devicerFs r __getitem__z!cuFFTPlanCacheManager.__getitem__`s !!33F; 19!8!8!::A%**BYBYB[A\]%%*G-  t{{ q KK  389P9P9R3S {{5!!rcXt|tjj|Sr )getattrrrHcurrent_devicer#names r __getattr__z!cuFFTPlanCacheManager.__getattr__ms!tEJJ5578$??rc|jr,t|tjj ||St |||Sr )rBsetattrrrHrSsuper __setattr__)r#rUvalue __class__s rrZz!cuFFTPlanCacheManager.__setattr__ps?   4 9 9 ;tjjS)z .. warning:: This flag is beta and subject to change. Returns whether flash scaled dot product attention is enabled or not. )rr_get_flash_sdp_enabledrrrrrs 88 * * ,,renabledcBtjj|y)z| .. warning:: This flag is beta and subject to change. Enables or disables flash scaled dot product attention. N)rr_set_sdp_use_flashr|s rrrs  HH(rc>tjjS)z .. warning:: This flag is beta and subject to change. Returns whether memory efficient scaled dot product attention is enabled or not. )rr_get_mem_efficient_sdp_enabledrrrrrs 88 2 2 44rcBtjj|y)z .. warning:: This flag is beta and subject to change. Enables or disables memory efficient scaled dot product attention. N)rr_set_sdp_use_mem_efficientrs rrrs  HH''0rc>tjjS)z .. warning:: This flag is beta and subject to change. Returns whether math scaled dot product attention is enabled or not. )rr_get_math_sdp_enabledrrrrrs 88 ) ) ++rcBtjj|y)z{ .. warning:: This flag is beta and subject to change. Enables or disables math scaled dot product attention. N)rr_set_sdp_use_mathrs rrrs  HHw'rparamsdebugcBtjj||S)aCheck if FlashAttention can be utilized in scaled_dot_product_attention. Args: params: An instance of SDPAParams containing the tensors for query, key, value, an optional attention mask, dropout rate, and a flag indicating if the attention is causal. debug: Whether to logging.warn debug information as to why FlashAttention could not be run. Defaults to False. Returns: True if FlashAttention can be used with the given parameters; otherwise, False. Note: This function is dependent on a CUDA-enabled build of PyTorch. It will return False in non-CUDA environments. )rr_can_use_flash_attentionrrs rrr s" 88 , ,VU ;;rcBtjj||S)aCheck if efficient_attention can be utilized in scaled_dot_product_attention. Args: params: An instance of SDPAParams containing the tensors for query, key, value, an optional attention mask, dropout rate, and a flag indicating if the attention is causal. debug: Whether to logging.warn with information as to why efficient_attention could not be run. Defaults to False. Returns: True if efficient_attention can be used with the given parameters; otherwise, False. Note: This function is dependent on a CUDA-enabled build of PyTorch. It will return False in non-CUDA environments. )rr _can_use_mem_efficient_attentionrs rrr s" 88 4 4VU CCr enable_flash enable_mathenable_mem_efficientc#"Kt}t}t} t|t |t |it|t |t |y#t|t |t |wxYww)a .. warning:: This flag is beta and subject to change. This context manager can be used to temporarily enable or disable any of the three backends for scaled dot product attention. Upon exiting the context manager, the previous state of the flags will be restored. N)rrrrrr)rrrprevious_flashprevious_mem_efficient previous_maths rrr4sy-.N#<#>*,M'& !56 $( !78 & ( !78 &sB%A)"B)#B  Br )F)TTT)( contextlibtypingrr__all__rrrrrrrvDefaultCusolverMagmarsjoinkeysrtr,r torch._Crxr ryr r1rboolrrrrrrrcontextmanagerrr r rrrrs  . + + @@2#4#4L::*xx&&..''00 XX $ $ * * ii 4 4 67:>94 4ehh555 694 XX94xJ. - -)d)51d1,(T(