a d& @s*ddlZddlmZGdddejZdS)N)nncsFeZdZdfdd ZddZddZd d Zd d Zd dZZ S)LitEmaH.?Tcst|dks|dkr"tdi|_|dtj|tjd|d|rZtjdtjdntjdtjd| D]@\}}|j rt| d d }|j ||i||| jqtg|_dS) Ng?zDecay must be between 0 and 1decaydtype num_updatesr.)super__init__ ValueError m_name2s_nameregister_buffertorchtensorfloat32intnamed_parameters requires_gradreplaceupdateclonedetachdatacollected_params)selfmodelruse_num_upatesnameps_name __class__b/var/www/html/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/ema.pyrs  zLitEma.__init__cCs |`|dtjdtjddS)Nr rr)r rrrr)rr&r&r'reset_num_updatesszLitEma.reset_num_updatescCs|j}|jdkr:|jd7_t|jd|jd|j}d|}tt|}t|}|D]\}||jr|j |}|| ||||<|| |||||qh||j vshJqhWdn1s0YdS)Nr r) rr minrno_graddictr named_buffersrrtype_assub_)rrrone_minus_decaym_param shadow_paramskeysnamer&r&r'forwards       zLitEma.forwardcCs\t|}t|}|D]:}||jrH||j||j|jq||jvsJqdS)N)r-rr.rrcopy_r)rrr2r3r4r&r&r'copy_to2s    zLitEma.copy_tocCsdd|D|_dS)z Save the current parameters for restoring later. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be temporarily stored. cSsg|] }|qSr&)r).0paramr&r&r' Bz LitEma.store..N)r)r parametersr&r&r'store;sz LitEma.storecCs(t|j|D]\}}|j|jq dS)a Restore the parameters stored with the `store` method. Useful to validate the model with EMA parameters without affecting the original optimization process. Store the parameters before the `copy_to` method. After validation (or model saving), use this to restore the former parameters. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be updated with the stored parameters. N)ziprrr7)rr=c_paramr:r&r&r'restoreDs zLitEma.restore)rT) __name__ __module__ __qualname__rr(r6r8r>rA __classcell__r&r&r$r'rs   r)rrModulerr&r&r&r's