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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def invalid_pixel_mask(self):
 """ Returns a binary mask for the NaN- and zero-valued pixels. Serves as a mask for invalid pixels. Returns ------- :obj:`BinaryImage` Binary image where a pixel value greater than zero indicates an invalid pixel. """

        # init mask buffer
        mask = np.zeros([self.height, self.width, 1]).astype(np.uint8)

        # update invalid pixels
        zero_pixels = self.zero_pixels()
        nan_pixels = self.nan_pixels()
        mask[zero_pixels[:, 0], zero_pixels[:, 1]] = BINARY_IM_MAX_VAL
        mask[nan_pixels[:, 0], nan_pixels[:, 1]] = BINARY_IM_MAX_VAL
        return BinaryImage(mask, frame=self.frame)