def METHOD_NAME(args):
    # backward compatibility for older model checkpoints
    if hasattr(args, "no_tie_adaptive_proj"):
        # previous models defined --no-tie-adaptive-proj, so use the existence of
        # that option to determine if this is an "old" model checkpoint
        args.no_decoder_final_norm = True  # old models always set this to True
        if args.no_tie_adaptive_proj is False:
            args.tie_adaptive_proj = True
    if hasattr(args, "decoder_final_norm"):
        args.no_decoder_final_norm = not args.decoder_final_norm
    args.activation_fn = getattr(args, "activation_fn", "relu")
    args.dropout = getattr(args, "dropout", 0.1)
    args.attention_dropout = getattr(args, "attention_dropout", 0.0)
    args.activation_dropout = getattr(args, "activation_dropout", 0.0)
    args.relu_dropout = getattr(args, "relu_dropout", 0.0)
    args.decoder_embed_dim = getattr(args, "decoder_embed_dim", 512)
    args.decoder_output_dim = getattr(
        args, "decoder_output_dim", args.decoder_embed_dim
    )
    args.decoder_input_dim = getattr(args, "decoder_input_dim", args.decoder_embed_dim)
    args.decoder_ffn_embed_dim = getattr(args, "decoder_ffn_embed_dim", 2048)
    args.decoder_layers = getattr(args, "decoder_layers", 6)
    args.decoder_attention_heads = getattr(args, "decoder_attention_heads", 8)
    # Model training is not stable without this
    args.decoder_normalize_before = True
    args.no_decoder_final_norm = getattr(args, "no_decoder_final_norm", False)
    args.adaptive_softmax_cutoff = getattr(args, "adaptive_softmax_cutoff", None)
    args.adaptive_softmax_dropout = getattr(args, "adaptive_softmax_dropout", 0)
    args.adaptive_softmax_factor = getattr(args, "adaptive_softmax_factor", 4)
    args.no_token_positional_embeddings = getattr(
        args, "no_token_positional_embeddings", False
    )
    args.share_decoder_input_output_embed = getattr(
        args, "share_decoder_input_output_embed", False
    )
    args.character_embeddings = getattr(args, "character_embeddings", False)
    args.character_filters = getattr(
        args,
        "character_filters",
        "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]",
    )
    args.character_embedding_dim = getattr(args, "character_embedding_dim", 4)
    args.char_embedder_highway_layers = getattr(args, "char_embedder_highway_layers", 2)
    args.adaptive_input = getattr(args, "adaptive_input", False)
    args.adaptive_input_factor = getattr(args, "adaptive_input_factor", 4)
    args.adaptive_input_cutoff = getattr(args, "adaptive_input_cutoff", None)
    args.tie_adaptive_weights = getattr(args, "tie_adaptive_weights", False)
    args.tie_adaptive_proj = getattr(args, "tie_adaptive_proj", False)
    args.decoder_learned_pos = getattr(args, "decoder_learned_pos", False)
    args.decoder_layerdrop = getattr(args, "decoder_layerdrop", 0.0)
    args.decoder_layers_to_keep = getattr(args, "decoder_layers_to_keep", None)
    args.layernorm_embedding = getattr(args, "layernorm_embedding", False)
    args.no_scale_embedding = getattr(args, "no_scale_embedding", False)
    args.quant_noise_pq = getattr(args, "quant_noise_pq", 0.0)
    args.quant_noise_pq_block_size = getattr(args, "quant_noise_pq_block_size", 8)
    args.quant_noise_scalar = getattr(args, "quant_noise_scalar", 0.0)
    args.add_bos_token = getattr(args, "add_bos_token", False)