+
    É&j  ã                   ón   € ^ RI t ^ RI HtHt ^ RIHt ^ RIHt ^ RIHt ^ RI	H
t
Ht R.t ! R R]4      tR# )	é    N)ÚnanÚTensor)Úconstraints)ÚDistribution)Úbroadcast_all)Ú_NumberÚ_sizeÚUniformc                   ó\  a a€ ] tR t^t oRtRt]R 4       t]V3R lR l4       t]V3R lR l4       t	]V3R lR	 l4       t
]V3R
 lR l4       tRV3R lV 3R llltRV 3R llt]P                  ! R^ R7      R 4       t]P$                  ! 4       3V3R lR lltR tR tR tR tRtVtV ;t# )r
   a‹  
Generates uniformly distributed random samples from the half-open interval
``[low, high)``.

Example::

    >>> m = Uniform(torch.tensor([0.0]), torch.tensor([5.0]))
    >>> m.sample()  # uniformly distributed in the range [0.0, 5.0)
    >>> # xdoctest: +SKIP
    tensor([ 2.3418])

Args:
    low (float or Tensor): lower range (inclusive).
    high (float or Tensor): upper range (exclusive).
Tc                ó†   € R \         P                  ! V P                  4      R\         P                  ! V P                  4      /# )ÚlowÚhigh)r   Ú	less_thanr   Úgreater_thanr   ©Úselfs   &Ús/Users/jameslopez/projects/CWCArchive/cwc-podcast/.venv/lib/python3.14/site-packages/torch/distributions/uniform.pyÚarg_constraintsÚUniform.arg_constraints!   s6   € ð ”;×(Ò(¨¯©Ó3Ø”K×,Ò,¨T¯X©XÓ6ð
ð 	
ó    c                ó    <€ V ^8„  d   QhRS[ /# ©é   Úreturn©r   )ÚformatÚ__classdict__s   "€r   Ú__annotate__ÚUniform.__annotate__*   s   ø€ ÷ *ñ *‘fñ *r   c                óJ   € V P                   V P                  ,           ^,          # ©r   ©r   r   r   s   &r   ÚmeanÚUniform.mean)   s   € à—	‘	˜DŸH™HÕ$¨Õ)Ð)r   c                ó    <€ V ^8„  d   QhRS[ /# r   r   )r   r   s   "€r   r   r   .   s   ø€ ÷ ñ ‘fñ r   c                ó0   € \         V P                  ,          # ©N)r   r   r   s   &r   ÚmodeÚUniform.mode-   s   € äT—Y‘YÐr   c                ó    <€ V ^8„  d   QhRS[ /# r   r   )r   r   s   "€r   r   r   2   s   ø€ ÷ 0ñ 0™ñ 0r   c                óJ   € V P                   V P                  ,
          R,          # )é   gªLXèz¶@r"   r   s   &r   ÚstddevÚUniform.stddev1   s   € à—	‘	˜DŸH™HÕ$¨Õ/Ð/r   c                ó    <€ V ^8„  d   QhRS[ /# r   r   )r   r   s   "€r   r   r   6   s   ø€ ÷ 2ñ 2™&ñ 2r   c                óh   € V P                   V P                  ,
          P                  ^4      ^,          # r!   )r   r   Úpowr   s   &r   ÚvarianceÚUniform.variance5   s%   € à—	‘	˜DŸH™HÕ$×)Ñ)¨!Ó,¨rÕ1Ð1r   c                ó^   <€ V ^8„  d   QhRS[ S[,          RS[ S[,          RS[R,          RR/# )r   r   r   Úvalidate_argsNr   )r   ÚfloatÚbool)r   r   s   "€r   r   r   9   sE   ø€ ÷ Cñ Cá‘e^ðCñ ‘unðCñ ˜d•{ð	Cð
 
ñCr   c                ó  <€ \        W4      w  V n        V n        \        V\        4      '       d-   \        V\        4      '       d   \
        P                  ! 4       pMV P                  P                  4       p\        SV `%  WCR 7       R# )©r5   N)
r   r   r   Ú
isinstancer   ÚtorchÚSizeÚsizeÚsuperÚ__init__)r   r   r   r5   Úbatch_shapeÚ	__class__s   &&&& €r   r?   ÚUniform.__init__9   s[   ø€ ô ,¨CÓ6ÑˆŒ$”)äcœ7×#Ò#¬
°4¼×(AÒ(AÜŸ*š*›,‰KàŸ(™(Ÿ-™-›/ˆKÜ‰Ñ˜ÐÖBr   c                ó,  <€ V P                  \        V4      p\        P                  ! V4      pV P                  P                  V4      Vn        V P                  P                  V4      Vn        \        \        V`#  VR R7       V P                  Vn	        V# )Fr9   )
Ú_get_checked_instancer
   r;   r<   r   Úexpandr   r>   r?   Ú_validate_args)r   r@   Ú	_instanceÚnewrA   s   &&& €r   rE   ÚUniform.expandG   st   ø€ Ø×(Ñ(¬°)Ó<ˆÜ—j’j Ó-ˆØ—(‘(—/‘/ +Ó.ˆŒØ—9‘9×#Ñ# KÓ0ˆŒÜŒgsÑ$ [ÀÐ$ÔFØ!×0Ñ0ˆÔØˆ
r   F)Úis_discreteÚ	event_dimc                óX   € \         P                  ! V P                  V P                  4      # r'   )r   Úintervalr   r   r   s   &r   ÚsupportÚUniform.supportP   s   € ô ×#Ò# D§H¡H¨d¯i©iÓ8Ð8r   c                ó&   <€ V ^8„  d   QhRS[ RS[/# )r   Úsample_shaper   )r	   r   )r   r   s   "€r   r   r   U   s   ø€ ÷ 8ñ 8¡Eð 8¹Vñ 8r   c                ó  € V P                  V4      p\        P                  ! W P                  P                  V P                  P
                  R 7      pV P                  W0P                  V P                  ,
          ,          ,           # ))ÚdtypeÚdevice)Ú_extended_shaper;   Úrandr   rS   rT   r   )r   rQ   ÚshaperV   s   &&  r   ÚrsampleÚUniform.rsampleU   sQ   € Ø×$Ñ$ \Ó2ˆÜzŠz˜%§x¡x§~¡~¸d¿h¹h¿o¹oÔNˆØx‰x˜$§)¡)¨d¯h©hÕ"6Õ7Õ7Ð7r   c                óÎ  € V P                   '       d   V P                  V4       V P                  P                  V4      P	                  V P                  4      pV P
                  P                  V4      P	                  V P                  4      p\        P                  ! VP                  V4      4      \        P                  ! V P
                  V P                  ,
          4      ,
          # r'   )
rF   Ú_validate_sampler   ÚleÚtype_asr   Úgtr;   ÚlogÚmul)r   ÚvalueÚlbÚubs   &&  r   Úlog_probÚUniform.log_probZ   s   € Ø××ÐØ×!Ñ! %Ô(ØX‰X[‰[˜Ó×'Ñ'¨¯©Ó1ˆØY‰Y\‰\˜%Ó ×(Ñ(¨¯©Ó2ˆÜyŠy˜Ÿ™ ›Ó$¤u§y¢y°·±¸T¿X¹XÕ1EÓ'FÕFÐFr   c                óÖ   € V P                   '       d   V P                  V4       WP                  ,
          V P                  V P                  ,
          ,          pVP	                  ^ ^R7      # )r   )ÚminÚmax)rF   r[   r   r   Úclamp©r   ra   Úresults   && r   ÚcdfÚUniform.cdfa   sM   € Ø××ÐØ×!Ñ! %Ô(ØŸ(™(Õ" t§y¡y°4·8±8Õ';Õ<ˆØ|‰|  qˆ|Ó)Ð)r   c                ón   € WP                   V P                  ,
          ,          V P                  ,           pV# r'   r"   rj   s   && r   ÚicdfÚUniform.icdfg   s%   € ØŸ)™) d§h¡hÕ.Õ/°$·(±(Õ:ˆØˆr   c                ód   € \         P                  ! V P                  V P                  ,
          4      # r'   )r;   r_   r   r   r   s   &r   ÚentropyÚUniform.entropyk   s   € ÜyŠy˜Ÿ™ T§X¡XÕ-Ó.Ð.r   r"   r'   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Úhas_rsampleÚpropertyr   r#   r(   r-   r2   r?   rE   r   Údependent_propertyrN   r;   r<   rX   rd   rl   ro   rr   Ú__static_attributes__Ú__classdictcell__Ú__classcell__)rA   r   s   @@r   r
   r
      sÕ   ù‡ € ñð  €Kàñ
ó ð
ð ÷*ó ð*ð ÷ó ðð ÷0ó ð0ð ÷2ó ð2÷Cõ C÷ð ×#Ò#°ÀÔCñ9ó Dð9ð -2¯JªJ«L÷ 8ò 8ò
Gò*ò÷/ò /r   )r;   r   r   Útorch.distributionsr   Ú torch.distributions.distributionr   Útorch.distributions.utilsr   Útorch.typesr   r	   Ú__all__r
   © r   r   Ú<module>r…      s0   ðó ß Ý +Ý 9Ý 3ß &ð ˆ+€ô^/ˆlö ^/r   