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@ -965,6 +965,16 @@ def run(rank, world_size, args):
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logging.info("About to create model")
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model = get_transducer_model(params)
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path = '/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_24layers.pt'
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pre_trained = torch.load(path)
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pre_trained_model = pre_trained["model"]
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#for n, p in model.named_parameters():
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# if 'layer' not in n:
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for n, p in pre_trained_model.items():
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print(n)
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num_param = sum([p.numel() for p in model.parameters()])
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logging.info(f"Number of model parameters: {num_param}")
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