text: class_mode: one of "binary", "categorical", "input", "multi_output", "raw", sparse" or None. Default: "categorical". Mode for yielding the targets: - "binary": 1D numpy array of binary labels, - "categorical": 2D numpy array of one-hot encoded labels. Supports multi-label output. - "input": images identical to input images (mainly used to work with autoencoders), - "multi_output": list with the values of the different columns, - "raw": numpy array of values in y_col column(s), - "sparse": 1D numpy array of integer labels, - None, no targets are returned (the generator will only yield batches of image data, which is useful to use in model.predict()).