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@ -1465,7 +1465,6 @@ def run_adapter(rank, world_size, args, wb=None):
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"""
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params = get_params()
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params.update(vars(args))
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#params.warm_step *= params.accum_grads
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fix_random_seed(params.seed)
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if world_size > 1:
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@ -1495,8 +1494,6 @@ def run_adapter(rank, world_size, args, wb=None):
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logging.info("About to create model")
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model = get_transducer_model(params)
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logging.info(model)
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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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