Ë
    þÍ:j  ã                   ó0   — d dl mZ 	 d	dededededdf
d„Zy)
é    )ÚTensorÚpredsÚtargetÚnum_outputsÚallow_1d_reshapeÚreturnNc                 ó„  — | j                   dkD  s|j                   dkD  r&t        d|j                   › d| j                   › d�«      ‚d}|s+|dk(  xr$ | j                   dk(  xs | j                  d   dk(   }|dkD  xr# | j                   dkD  xr || j                  d   k7  }|s|rt        d|› d| j                  d   › d�«      ‚y)	aœ  Check that predictions and target have the correct shape, else raise error.

    Args:
        preds: Predicted tensor
        target: Ground truth tensor
        num_outputs: Number of outputs in multioutput setting
        allow_1d_reshape: Allow that for num_outputs=1 that preds and target does not need to be 1d tensors. Instead
            code that follows are expected to reshape the tensors to 1d.

    é   zWExpected both predictions and target to be either 1- or 2-dimensional tensors, but got z and ú.Fé   zPExpected argument `num_outputs` to match the second dimension of input, but got N)ÚndimÚ
ValueErrorÚshape)r   r   r   r   Úcond1Úcond2s         ú}/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/torchmetrics/functional/regression/utils.pyÚ _check_data_shape_to_num_outputsr      sÚ   € ð ‡z�z�A‚~˜Ÿ™ qšÜðØŸ™�} E¨%¯*©*¨°Qð8ó
ð 	
ð €EÙØ˜qÑ ÒQ¨%¯*©*¸©/Ò*P¸U¿[¹[È¹^ÈqÑ=PÐ%QˆØ˜!‰OÒP §
¡
¨Q¡ÒP°;À%Ç+Á+ÈaÁ.Ñ3P€EÙ‘ÜØ^Ð_jÐ^kØ�E—K‘K ‘NÐ# 1ð&ó
ð 	
ð ó    )F)Útorchr   ÚintÚboolr   © r   r   ú<module>r      s>   ðõ ð OTñ
Øð
Ø!ð
Ø03ð
ØGKð
à	ô
r   