a  d @s(ddlmZdeeeeddddZdS))TensorFN)predstarget num_outputsallow_1d_reshapereturncCs|jdks|jdkr.td|jd|jdd}|sX|dkoV|jdkpT|jddk }|dkov|jdkov||jdk}|s|rtd|d|jdddS) aCheck 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. zWExpected both predictions and target to be either 1- or 2-dimensional tensors, but got z and .FzPExpected argument `num_outputs` to match the second dimension of input, but got N)ndim ValueErrorshape)rrrrZcond1Zcond2rq/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torchmetrics/functional/regression/utils.py _check_data_shape_to_num_outputss$ " r)F)Ztorchrintboolrrrrrs