funasr/train_utils/model_summary.py
@@ -1,4 +1,3 @@ import humanfriendly import numpy as np import torch @@ -59,12 +58,7 @@ message += ( f" Number of trainable parameters: {num_params} ({percent_trainable}%)\n" ) num_bytes = humanfriendly.format_size( sum( p.numel() * to_bytes(p.dtype) for p in model.parameters() if p.requires_grad ) ) message += f" Size: {num_bytes}\n" dtype = next(iter(model.parameters())).dtype message += f" Type: {dtype}" return message