Pi_$ddlZddlZddlZddlmZddlmZddl m Z m Z m Z ej dZdZGddZddZGd d ejZGd d ejZGd dejZdS)N)partial)OptionalCallableAnyjaxc|t|jvr5t|j|t|j|}n)||j||x}t|j|<|SN)varsmodulerng)concretenameshapedtypeinittensors c/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/einx/nn/equinox.pycreate_or_retriever so tHO$$$$ho)>)>t)D)Pho&&t,/3tHL%/O/OOho&&t, MceZdZGddejjjZGddejjjZGddejj Z dS) ParamFactoryceZdZdZdZdS)ParamFactory.Concretec||_||_||_|t|dr|j}nd}||_||_dS)Nrfloat32)r rrhasattrrr )selfr rrrr s r__init__zParamFactory.Concrete.__init__sN DKDIDI}67++&"LEE%EDJDHHHrc\|t|j|j|jfSr )rCacheKeyrrrrs rto_value_and_keyz&ParamFactory.Concrete.to_value_and_key%s%..ty$)TZPPP PrN)__name__ __module__ __qualname__rr"rrConcreters7    Q Q Q Q Qrr'c&eZdZdZdZdZdZdS)ParamFactory.CacheKeyc0||_||_||_dSr rrrrrrrs rrzParamFactory.CacheKey.__init__)DIDIDJJJrcDt|j|j|jfSr )hashrrrr!s r__hash__zParamFactory.CacheKey.__hash__.sDItz:;; ;rct|tjo/|j|jko|j|jko|j|jkSr ) isinstancerr rrr)rothers r__eq__zParamFactory.CacheKey.__eq__1sL5,"788.I+.I+.J%+-  rc`t|j|j|j}||fSr )rTracerrrr)rbackend virtual_argxs r to_tracerzParamFactory.CacheKey.to_tracer9s(##DIty$*EEAa4KrN)r#r$r%rr0r4r:r&rrr r)(sP     < < <        rr ceZdZdZdZdS)ParamFactory.Tracerc0||_||_||_dSr r+r,s rrzParamFactory.Tracer.__init__>r-rc|j|jn|dd}|j|jn|dd}|j|jn|dd}|t d|t dt |t r|dks|dkr&tjj d }n|d kr'tjj d | }n|d kr'tjj d| }n|dkr9tjj |d|d|d}nUt d|dt |ttfr&tjj || }tjt$|||||gtj|S)Nrrrz/Must specify name for tensor factory eqx.Modulez/Must specify init for tensor factory eqx.Moduleget_at rearrangeg{Gz?)stddevaddg)rmultiplyg?dotin_axisout_axis batch_axisz3Don't know which initializer to use for operation '')argsoutput)rgetrr ValueErrorr2strtjaxnn initializersnormalconstant lecun_normalintfloateinxtracerapplyrTensor)rrkwargsrrrs r__call__zParamFactory.Tracer.__call__Cs$(I$54996::fd;S;SD$(I$54996::fd;S;SD&*j&8DJJfjjRV>W>WE| !RSSS| !RSSSD#&& H8##t{':':7/66d6CCDDU]]7/88E8JJDDZ''7/88E8JJDDU]]7/<<y)6*+=vl?SDD%%b[_%b%b%bcccD3,// Hw+44T4GG;$$"D%5{))%00% rN)r#r$r%rr[r&rrr6r<=s2         rr6N) r#r$r%rVrWinputInputr'r TensorFactoryr6r&rrrrsQQQQQ4;$*QQQ$4;$-*$$$$$*$$$$$rrc>t|||||S)aCreate a tensor factory for Equinox parameters. Args: module: The module to create the parameter in. Must be an instance of ``eqx.Module``. name: Name of the parameter. If ``None``, uses a default name determined from the calling operation. Defaults to ``None``. init: Initializer for the parameter. If ``None``, uses a default init method determined from the calling operation. Defaults to ``None``. dtype: Data type of the parameter. If ``None``, uses the ``dtype`` member of the calling module or ``float32`` if it does not exist. Defaults to ``None``. Returns: A tensor factory with the given default parameters. )rr')r rrrr s rparamr`ds   tUC @ @@rc*eZdZUdZeed<eed<eed<eed<eed<eed<eej ed<eej ed <ee ed <e ed <eed <eed <e ed< ddededededed ed ee d e d ed e de fdZ ddZdS)NormaNormalization layer. Args: stats: Einstein string determining the axes along which mean and variance are computed. Will be passed to ``einx.reduce``. params: Einstein string determining the axes along which learnable parameters are applied. Will be passed to ``einx.elementwise``. Defaults to ``"b... [c]"``. mean: Whether to apply mean normalization. Defaults to ``True``. var: Whether to apply variance normalization. Defaults to ``True``. scale: Whether to apply a learnable scale according to ``params``. Defaults to ``True``. bias: Whether to apply a learnable bias according to ``params``. Defaults to ``True``. epsilon: A small float added to the variance to avoid division by zero. Defaults to ``1e-5``. fastvar: Whether to use a fast variance computation. Defaults to ``True``. dtype: Data type of the weights. Defaults to ``"float32"``. decay_rate: Decay rate for exponential moving average of mean and variance. If ``None``, no moving average is applied. Defaults to ``None``. **kwargs: Additional parameters that specify values for single axes, e.g. ``a=4``. statsparamsmeanvar use_scaleuse_biasscalebias decay_rateepsilonfastvarrrZb... 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