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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 load_coco(image_set, dirname, shuffle=False):
 """ wrapper function for loading ms coco dataset Parameters: image_set : str train2014, val2014, valminusminival2014, minival2014 dirname: str root dir for coco shuffle: boolean initial shuffle """

    anno_files = ['instances_' + y.strip() + '.json' for y in image_set.split(',')]
    assert anno_files, "No image set specified"
    imdbs = []
    for af in anno_files:
        af_path = os.path.join(dirname, 'annotations', af)
        imdbs.append(Coco(af_path, dirname, shuffle=shuffle))
    if len(imdbs) > 1:
        return ConcatDB(imdbs, shuffle)
    else:
        return imdbs[0]