+j;&ddlmZddlZddlZddlZddlZddlZddlZddlm Z ddl m Z ddl m Z ddlmZerddlmZejeZd+d Zd,d Zd-dZd.dZ d/dddddddd0d&Ze d'Ze ejfd(Zd)Zgd*ZdS)1) annotationsN)Callable)contextmanager)isclass) TYPE_CHECKING)Tensorreturnstrct|s|j}|j}||tjjkr|jS|dz|jzS)aI Gives a full name (package_name.class_name) for a class / object in Python. Will be used to load the correct classes from JSON files Args: obj: The object for which to get the full name, e.g. an instance of a class or the class itself. Returns: str: The full name of the object. Example: >>> from sentence_transformers.sentence_transformer.losses import MultipleNegativesRankingLoss >>> from sentence_transformers import SentenceTransformer >>> from sentence_transformers.util import fullname >>> model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2') >>> loss = MultipleNegativesRankingLoss(model) >>> fullname(loss) 'sentence_transformers.sentence_transformer.losses.multiple_negatives_ranking.MultipleNegativesRankingLoss' N.)r __class__ __module__r __name__)objmodules MC:\Projects\DSCons\.venv\Lib\site-packages\sentence_transformers\util\misc.pyfullnamersM( 3<<m ^F ~3=#;;;| C<#, &&similarity_fctrct|tjrot|jdt |jj}dd|j D}|r|d|dn|St|dd}t|dt |j}|dvr?t|d r/d d l m }|d kr|j n|j}||jjSt|d d}|Add| D}|d|dS|S)zReadable config-dict rendering of a loss's scoring callable: objects exposing ``get_config_dict`` (e.g. configured metric classes) and :func:`functools.partial` bindings include their settings.rz, c3*K|]\}}|d|VdS=N.0keyvalues r z&similarity_fct_name..6s4^^ UC++%++^^^^^^r()__self__N) similaritysimilarity_pairwisesimilarity_fn_namer)SimilarityFunctionr#get_config_dictc3*K|]\}}|d|VdSrrrs rrz&similarity_fct_name..Gs4VV UC++%++VVVVVVr) isinstance functoolspartialgetattrfunctyperjoinkeywordsitemshasattr%sentence_transformers.util.similarityr&to_similarity_fnto_similarity_pairwise_fnr%)rnameargsownerr&resolve metric_configs rsimilarity_fct_namer;0s.)"3443~*J^=P8Q8Q8Z[[yy^^n>U>[>[>]>]^^^^^$(2$      d2 NJ 5 5E >:tN/C/C/L M MD 444H\9]9]4LLLLLL|##  / /#=  wu/0099N,=tDDM yyVVmmoo>S>S>U>UVVVVV      Krteacher_probabilitiesrteacher_logitsteacher_temperaturefloat loss_nameNonec|}|rt |d|rdSt |dk}|sdS|dj | dj z  }t |d|d|d|d |d d |d z d d dS)aInspect a distillation loss's teacher target once, on its first forward. Takes the target the loss itself computed rather than recomputing a softmax, so the two can never disagree. Reading either result off an accelerator costs a device synchronization, hence the once-per-loss contract. That also means only the first batch a loss sees is inspected: with one loss shared across a ``DatasetDict`` whose splits carry differently scaled teacher scores, the splits drawn later go unexamined. Args: teacher_probabilities: The softmaxed teacher target the loss will use. teacher_logits: The raw teacher scores, used to report their spread. teacher_temperature: The temperature already applied to ``teacher_logits``. loss_name: Loss class name, to open the message with. Raises: ValueError: If the teacher scores contain NaN, which would make the loss and every gradient NaN on the first backward. z: the teacher scores contain NaN, so the loss and every gradient would be NaN after the first backward. Check the column holding your teacher scores.Nr)dimz: teacher_temperature=z underflows z of zg teacher scores to exactly zero, so those candidates carry no gradient. The widest candidate row spans z.1fz, and a float32 softmax underflows once a row's spread divided by the temperature exceeds about 100. Raise teacher_temperature above dz.3gr )detachr?isnanany ValueErrorisinfintsummaxvaluesminitemloggerwarningnumel)r<r=r>r@scores collapsedspreads rcheck_teacher_targetsrWLs* " " $ $ * * , ,F ||~~  Z Z Z   ||~~*a/446677I jjRj  '&****<*<*CC H H J J O O Q QF NN  9 9,? 9 9Y 9 9 & & ( ( 9 97=f 9 9&,c\8  9 9 9r dotted_pathr.c |dd\}}n"#t$r|d}t|wxYwtj5tjdt  tj|}n$#t$rtj|}YnwxYwdddn #1swxYwY t||S#t$rd|d|d}t|wxYw) a} Import a dotted module path and return the attribute/class designated by the last name in the path. Raise ImportError if the import failed. Args: dotted_path (str): The dotted module path. Returns: Any: The attribute/class designated by the last name in the path. Raises: ImportError: If the import failed. Example: >>> import_from_string('sentence_transformers.sentence_transformer.losses.multiple_negatives_ranking.MultipleNegativesRankingLoss') r z doesn't look like a module pathignoreNzModule "z" does not define a "z" attribute/class) rsplitrI ImportErrorwarningscatch_warnings simplefilterDeprecationWarning importlib import_module Exceptionr,AttributeError)rX module_path class_namemsgrs rimport_from_stringriwsp$"-"4"4S!"<"< ZZ >>>#  " "::h(:;;; :,[99FF : : :,[99FFF : :::::::::::::::vz*** XXX:XXX#sJ;B2-BB2B# B2"B##B22B69B6>C#C1F)trust_remote_coderevision code_revisiontoken cache_folderlocal_files_only class_refmodel_name_or_path str | Nonerjboolrkrlrmbool | str | Nonernroc |drt|S|ddlm}|s\tj|rtj|nd|} td|d|d| d  |||||||| S#ttf$rYnwxYwt|S) at Resolve a module class reference to a class object. For class refs in the ``sentence_transformers.*`` namespace, this imports directly via :func:`import_from_string`. For other class refs (e.g. repository-local custom classes like ``modeling_my_model.CustomTransformer``), it first tries :func:`transformers.dynamic_module_utils.get_class_from_dynamic_module` to fetch the modeling file from the model directory, then falls back to :func:`import_from_string` if dynamic loading is not applicable or fails. Importing a class outside the ``sentence_transformers.*`` namespace runs code selected by the model's configuration (repository-hosted modeling code via dynamic loading, or a locally installed package via direct import). Loading such a class requires ``trust_remote_code=True``, for local directories just like for Hugging Face Hub repositories. .. versionchanged:: 6.0 Importing a module class outside the ``sentence_transformers.*`` namespace now requires ``trust_remote_code=True`` whenever ``model_name_or_path`` is set. Previously a local ``model_name_or_path`` was implicitly trusted, and untrusted imports emitted a ``FutureWarning`` while still importing. Args: class_ref: Dotted class path. Either a fully-qualified ``sentence_transformers.*`` path or a repository-local reference like ``modeling_.``. model_name_or_path: Hub repo id or local directory used to source repository-local modeling files. Required for dynamic loading. trust_remote_code: Whether to trust and import code selected by the model configuration. Required to import any non-``sentence_transformers.*`` class when ``model_name_or_path`` is set, and permits dynamic loading of repository-hosted modeling files. Any falsy value, an explicit None included, is treated as False. revision: Hub revision to fetch the modeling file from. code_revision: Optional separate revision pinning for the modeling code (overrides ``revision`` when set). token: Hugging Face Hub authentication token. Required for fetching modeling files from private repositories. cache_folder: Optional override for the Hugging Face Hub cache directory. local_files_only: If True, only use cached files and never reach out to the Hub. Returns: The resolved class. Raises: ValueError: If ``class_ref`` is outside the ``sentence_transformers.*`` namespace, ``model_name_or_path`` is set, and ``trust_remote_code`` is not True. zsentence_transformers.Nr)get_class_from_dynamic_modulezhttps://hf.co/z The model z references the module class z, which is not part of Sentence Transformers. Importing it executes third-party code. You can inspect the repository content at zS. 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