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""" x: Input data. It could be: - A Numpy array (or array-like), or a list of arrays (in case the model has multiple inputs). - A TensorFlow tensor, or a list of tensors (in case the model has multiple inputs). - A dict mapping input names to the corresponding array/tensors, if the model has named inputs. - A `tf.data` dataset. Should return a tuple of either `(inputs, targets)` or `(inputs, targets, sample_weights)`. - A generator or `keras.utils.Sequence` returning `(inputs, targets)` or `(inputs, targets, sample weights)`. A more detailed description of unpacking behavior for iterator types (Dataset, generator, Sequence) is given below. y: Target data. Like the input data `x`, it could be either Numpy array(s) or TensorFlow tensor(s). It should be consistent with `x` (you cannot have Numpy inputs and tensor targets, or inversely). If `x` is a dataset, generator, or `keras.utils.Sequence` instance, `y` should not be specified (since targets will be obtained from `x`)."""
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