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@ -982,7 +982,6 @@ def run(rank, world_size, args):
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transducer_model.load_state_dict(pre_trained_model, strict=True)
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model = get_interformer_model(transducer_model.encoder, params)
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print(model)
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'''
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for n, p in model.named_parameters():
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if 'layer' not in n:
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@ -998,7 +997,6 @@ def run(rank, world_size, args):
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else:
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print(f'skipping param load {n}')
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'''
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exit()
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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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