U Mh- @sddlZddlmZddlmZmZmZdgZdddZedd Z ed d Z ed d Z eddZ ddZ eeeeeedddZeeefeddddZdS)N)repeat)ListDictAny'consume_prefix_in_state_dict_if_presentparsecsfdd}||_|S)Ncs$t|tjjrt|Stt|SN) isinstance collectionsabcIterabletupler)xnH/var/www/html/venv/lib/python3.8/site-packages/torch/nn/modules/utils.pyr sz_ntuple..parse)__name__)rnamerrrr_ntuple s r_single_pair_triple _quadruplecstfddt|DS)zReverse the order of `t` and repeat each element for `n` times. This can be used to translate padding arg used by Conv and Pooling modules to the ones used by `F.pad`. c3s |]}tD] }|VqqdSr)range).0r_rrr s z(_reverse_repeat_tuple..)r reversed)trrrr_reverse_repeat_tuplesr$)out_sizedefaultsreturncCsdddl}t|t|jfr|St|t|krBtdt|dddt||t| dDS)Nrz#Input dimension should be at least rcSs g|]\}}|dk r|n|qSrr)rvdrrr *sz&_list_with_default..)torchr intZSymIntlen ValueErrorzip)r%r&r+rrr_list_with_default"sr0) state_dictprefixr'cCst|}|D],}||r|t|d}||||<qt|drt|j}|D]N}t|dkrlqZ||ddks||rZ|t|d}|j||j|<qZdS)aStrip the prefix in state_dict in place, if any. ..note:: Given a `state_dict` from a DP/DDP model, a local model can load it by applying `consume_prefix_in_state_dict_if_present(state_dict, "module.")` before calling :meth:`torch.nn.Module.load_state_dict`. Args: state_dict (OrderedDict): a state-dict to be loaded to the model. prefix (str): prefix. N _metadatar.)listkeys startswithr-pophasattrr3replace)r1r2r7keyZnewkeyrrrr/s    )r)r itertoolsrtypingrrr__all__rrrrrr$r,r0strrrrrrs