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Disable decoder layers in pretrained.py if it is not used.
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@ -226,7 +226,13 @@ def main():
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args = parser.parse_args()
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params = get_params()
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if args.method != "attention-decoder":
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# to save memory as the attention decoder
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# will not be used
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params.num_decoder_layers = 0
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params.update(vars(args))
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logging.info(f"{params}")
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device = torch.device("cpu")
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@ -248,7 +254,7 @@ def main():
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)
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checkpoint = torch.load(args.checkpoint, map_location="cpu")
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model.load_state_dict(checkpoint["model"])
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model.load_state_dict(checkpoint["model"], strict=False)
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model.to(device)
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model.eval()
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