o Ni@sHddlmZddlZddlmZddlZddlmZGdddeZdS)) annotationsN) OrderedDict)ModulecseZdZdZd$d%fdd Zdd Zd d Zd d ZddZddZ ddZ ddZ ddZ ddZ ddZddZddZd d!Zd"d#ZZS)& BufferDictaq Holds buffers in a dictionary. BufferDict can be indexed like a regular Python dictionary, but buffers it contains are properly registered, and will be visible by all Module methods. `torch.nn.BufferDict` is an **ordered** dictionary that respects * the order of insertion, and * in `torch.nn.BufferDict.update`, the order of the merged `OrderedDict` or another `torch.nn.BufferDict` (the argument to `torch.nn.BufferDict.update`). Note that `torch.nn.BufferDict.update` with other unordered mapping types (e.g., Python's plain `dict`) does not preserve the order of the merged mapping. Args: buffers (iterable, optional): a mapping (dictionary) of (string : `torch.Tensor`) or an iterable of key-value pairs of type (string, `torch.Tensor`) ```python class MyModule(nn.Module): def __init__(self): super().__init__() self.buffers = nn.BufferDict({"left": torch.randn(5, 10), "right": torch.randn(5, 10)}) def forward(self, x, choice): x = self.buffers[choice].mm(x) return x ``` NF persistentboolcs*t||_|dur||dSdS)z Args: buffers (`dict`): A mapping (dictionary) from string to `torch.Tensor`, or an iterable of key-value pairs of type (string, `torch.Tensor`). N)super__init__rupdate)selfbuffersr __class__L/home/ubuntu/.local/lib/python3.10/site-packages/peft/tuners/_buffer_dict.pyr 2s zBufferDict.__init__cCs |j|SN_buffersr keyrrr __getitem__? zBufferDict.__getitem__cCs|j|||jddS)N)r)register_bufferr)r rbufferrrr __setitem__BszBufferDict.__setitem__cCs |j|=dSrrrrrr __delitem__Es zBufferDict.__delitem__cCs t|jSr)lenrr rrr__len__HrzBufferDict.__len__cCst|jSr)iterrkeysrrrr__iter__KszBufferDict.__iter__cCs ||jvSrrrrrr __contains__NrzBufferDict.__contains__cCs|jdS)z%Remove all items from the BufferDict.N)rclearrrrrr#QszBufferDict.clearcCs||}||=|S)zRemove key from the BufferDict and return its buffer. Args: key (`str`): Key to pop from the BufferDict r)r rvrrrpopUszBufferDict.popcC |jS)z*Return an iterable of the BufferDict keys.)rr rrrrr ` zBufferDict.keyscCr&)z5Return an iterable of the BufferDict key/value pairs.)ritemsrrrrr(dr'zBufferDict.itemscCr&)z,Return an iterable of the BufferDict values.)rvaluesrrrrr)hr'zBufferDict.valuescCst|tjjstdt|jt|ttfr&| D]\}}|||<qd St|tjj r>t | D]\}}|||<q3d St |D]:\}}t|tjjs\tdt |dt|jt|dksttdt |dt t|d|d||d<qBd S) a  Update the `torch.nn.BufferDict` with the key-value pairs from a mapping or an iterable, overwriting existing keys. Note: If `buffers` is an `OrderedDict`, a `torch.nn.BufferDict`, or an iterable of key-value pairs, the order of new elements in it is preserved. Args: buffers (iterable): a mapping (dictionary) from string to `torch.Tensor`, or an iterable of key-value pairs of type (string, `torch.Tensor`). zQBuffersDict.update should be called with an iterable of key/value pairs, but got z$BufferDict update sequence element #z should be Iterable; isz has length z; 2 is requiredrN) isinstance collectionsabcIterable TypeErrortype__name__rrr(Mappingsorted enumeratestrr ValueError)r r rrjprrrr lsB    zBufferDict.updatec Csg}|jD]@\}}ddd|D}|jj}|dkr!dn d|d|d}d t |d ||d }| d |d |qd|}|S)Nxcss|]}t|VqdSr)r6).0sizerrr sz(BufferDict.extra_repr..cpuz ( )zBuffer containing: [z of size ]z (z):  ) rr(joinr<devicer1upper get_devicetorchtypenameappend) r child_lineskr9size_str device_type device_strparastrtmpstrrrr extra_reprs& zBufferDict.extra_reprcCstd)Nz BufferDict should not be called.) RuntimeError)r inputrrr__call__szBufferDict.__call__)NF)rr)r2 __module__ __qualname____doc__r rrrrr!r"r#r%r r(r)r rRrU __classcell__rrr rrs"  ' r) __future__rr-rrHtorch.nnrrrrrrs