\!hnSSKrSSjrg)Nc US:Xd [U[5(d [S5e[U[5(a[R "U5nOUn[ UR5S:Xd [S5eUS:Xa[R"US-5nOUnUS:Xa[R"S//US9nO;[R"[ U5U45n[U5H upgSXVU4'M URU5$)aOne-hot encoding of class labels Parameters ---------- y : array-like, shape = [n_classlabels] Python list or numpy array consisting of class labels. num_labels : int or 'auto' Number of unique labels in the class label array. Infers the number of unique labels from the input array if set to 'auto'. dtype : str NumPy array type (float, float32, float64) of the output array. Returns ---------- ary : numpy.ndarray, shape = [n_classlabels] One-hot encoded array, where each sample is represented as a row vector in the returned array. Examples ---------- For usage examples, please see https://rasbt.github.io/mlxtend/user_guide/preprocessing/one_hot/ autoz'num_labels must be an integer or "auto"zy array must be 1-dimensionalg)dtype) isinstanceintAttributeErrorlistnpasarraylenshapemaxarrayzeros enumerateastype)y num_labelsrytuniqaryivals oC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\mlxtend/preprocessing/onehot.pyone_hotr s2 & Jz3$?$?FGG!T ZZ]  rxx=A <==Vvvb1f~ qyhhwe,hhA~&lFAC3K# ::e )rfloat)numpyr rrrr!s.r