o i0@sBdZddlZddlZddlZddlmZdejjdefddZ dS)z/Initialize modules for espnet2 neural networks.N)check_argument_typesmodelinitc CstsJ|dkr|D]z\}}|j}d|vr,|dkr,|td|dq |dkrE|d}dt |}| d|q |dkr^|d}dt |}| d|q |d vr|d}|dd D]}||9}qqdt |}| d|q t | D]_}t |tjjr|jj ddnDt |tjjr|jd}|jj|d |ddn't |tjjr|D]\}} d |vr| d}| j|d |ddqt|d r|qd S|D]K}|dkr=|dkr tjj|jq|dkrtjj|jq|dkr'tjjj|jddq|dkr7tjjj|jddqtd|q|D]\}}d|vr`|dkr`|jtd|dqB| D] } t | tjjtjjtjj fr{| !t| d r| qft"|dd rt"|j#dd r|j#$t"|dd rt"|j%dd r|j%$n.t t"|j%dd tjj&rt't"|j%dD]\} } t"|j%j(| dd r|j%j(| $qt"|dd rt"|j)dd r|j)$d Sd Sd S)aQInitialize weights of a neural network module. Parameters are initialized using the given method or distribution. Custom initialization routines can be implemented into submodules as function `espnet_initialization_fn` within the custom module. Args: model: Target. init: Method of initialization. chainerz.biasz Initialize z to zerosrg?)Nr biasespnet_initialization_fnxavier_uniform xavier_normalkaiming_uniformrelu) nonlinearitykaiming_normalzUnknown initialization: encoderreload_pretrained_parametersfrontend frontends postencoder)*rnamed_parametersdatadimzero_logginginfosizemathsqrtnormal_NotImplementedErrormodules isinstancetorchnn Embeddingweight RNNCellBasebias_ihfill_RNNBasehasattrr parametersrxavier_uniform_xavier_normal_kaiming_uniform_kaiming_normal_ ValueError LayerNorm GroupNormreset_parametersgetattrrrr ModuleList enumeraterr) rrnameprnstdvkmodparammi_rCR/home/ubuntu/.local/lib/python3.10/site-packages/espnet2/torch_utils/initialize.py initialize s                           rE) __doc__rrr$ typeguardrr%ModulestrrErCrCrCrDs