o i @sJddlZddlZdedefddZdefddZdejjdefd d Z dS) NnumberreturncCs|dksJgd}t|dkrtt|dnd}tt|d}t|t|}d|d}|d|}|d}|dd||S) abReturn human_readable_count Originated from: https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/core/memory.py Abbreviates an integer number with K, M, B, T for thousands, millions, billions and trillions, respectively. Examples: >>> get_human_readable_count(123) '123 ' >>> get_human_readable_count(1234) # (one thousand) '1 K' >>> get_human_readable_count(2e6) # (two million) '2 M' >>> get_human_readable_count(3e9) # (three billion) '3 B' >>> get_human_readable_count(4e12) # (four trillion) '4 T' >>> get_human_readable_count(5e15) # (more than trillion) '5,000 T' Args: number: a positive integer number Return: A string formatted according to the pattern described above. r) KMBT z.2fr)intnpfloorlog10ceilminlen)rlabels num_digits num_groupsshiftindexrT/home/ubuntu/.local/lib/python3.10/site-packages/funasr/train_utils/model_summary.pyget_human_readable_counts $  rcCstt|dddS)N)r str)dtyperrrto_bytes*sr modelc Csd}|t|7}d\}}|D]%\}}td||j|j|j|j|||7}|jr5||7}qd|d|}t |}t |}|d7}|d|j j d7}|d |d7}|d |d |d 7}t t |j}|d |7}|S)NzModel structure: )rrzDname: {}, dtype: {}, device: {}, trainable: {}, shape: {}, numel: {}z{:.1f}gY@z Model summary: z Class Name:  z& Total Number of model parameters: z$ Number of trainable parameters: z (z%) z Type: )rnamed_parametersprintformatrdevice requires_gradshapenumelr __class____name__nextiter parameters)r!message tot_params num_paramsnameparampercent_trainablerrrr model_summary/s.   r5) numpyrtorchr rrr nnModuler5rrrrs %