
    h                     n   S SK r S SKJr   S SKrS SKrS SKrSr\R                  r\" \R                  5      r	 \R                  R                  R                  5         Sr\	R                  S:  a  \R                   rO\R$                  r  S SKrS SKrSr\R                  R1                  5       S :g  r\" \R6                  S5      =(       a$    \R6                  R8                  R;                  5       r\=(       a$    \R6                  R8                  R?                  5       r \r!\" \"" \R                  5      5      r#\#\" S5      :  =(       a3    \R                  RH                  RJ                  RM                  5       (       + r'S	 r(Sq)Sq*Sq+S
 r,Sq-Sq. S SK/r/ S SK0r0Sr1\=(       d    \ r2/ SQr3g! \R                  R                  R                   a    Sr GNqf = f! \\4 a    SrSrSr\" S5      r	SrSrSr GNjf = f! \ a    SrSrSrSr!SrSr Sr'\" S5      r# Nf = f! \ a    Sr/ Nf = f! \ a    Sr0Sr1 Nf = f)    N)VersionTF
   z0.0.0mpsz1.9.0c                      Sn [         R                  " U [        5        SS KqSS KqSq[        [        R                  R                  S5      5      S:  q	g )NzBuilt-in TensorFlow support will be removed in Thinc v9. If you need TensorFlow support in the future, you can transition to using a custom copy of the current TensorFlowWrapper in your package or project.r   TGPU)
warningswarnDeprecationWarning
tensorflowtensorflow.experimental.dlpackhas_tensorflowlenconfigget_visible_deviceshas_tensorflow_gpuwarn_msgs    F/home/james-whalen/.local/lib/python3.13/site-packages/thinc/compat.pyenable_tensorflowr   ;   sI    	  MM(./)NZ..BB5IJQN    c                  J    Sn [         R                  " U [        5        SS KqSqg )NzBuilt-in MXNet support will be removed in Thinc v9. If you need MXNet support in the future, you can transition to using a custom copy of the current MXNetWrapper in your package or project.r   T)r   r	   r
   mxnet	has_mxnetr   s    r   enable_mxnetr   P   s%    	  MM(./Ir   )cupycupyxtorchr   r   h5pyos_signpost)4r   packaging.versionr   r   cupy.cublasr   has_cupycublas__version__cupy_versioncudaruntimegetDeviceCounthas_cupy_gpuCUDARuntimeErrormajorfrom_dlpackcupy_from_dlpack
fromDlpackImportErrorAttributeErrorr   torch.utils.dlpack	has_torchdevice_counthas_torch_cuda_gpuhasattrbackendsr   is_builthas_torch_mpsis_availablehas_torch_mps_gpuhas_torch_gpustrtorch_versionampcommonamp_definitely_not_availablehas_torch_ampr   r   r   r   r   r   r   r   r   has_os_signposthas_gpu__all__ r   r   <module>rF      s`    %H[[F4++,L		((* R++??%I002a7ENNE2Tu~~7I7I7R7R7TM%K%..*<*<*I*I*K&MC 1 123M)) 	E

%%BBDD O  
  		
O 
++G 99--  	^$ FDE7#LHL0  %EIMMMG$M%h  D  KOsq   ,G &F' G <G 
C1G7 H H' '&GG GG G43G47HHH$#H$'
H43H4