ik ddlmZmZddlmZmZmZmZmZddl Z ddl m Z m Z ddl m Z ddlmZddlmZddlmZmZ dd e d ee d efd eed e fdZGddeeZy))ABCabstractmethod)AnyCallableListOptionalUnionN)Tensortensor)Literal)Metric)_check_retrieval_inputs)_flexible_bincount dim_zero_catvalues aggregationmeanmedianminmaxdimreturnc|dk(r$||jS|j|S|dk(r.||jS|j|jS|dk(r.||jS|j|jS|dk(r.||j S|j |jS|||S)z9Aggregate the final retrieval values into a single value.rrrrr)rrrrr)rrrs p/Volumes/fast/ai/experiments/voice-extract-mac/.venv/lib/python3.12/site-packages/torchmetrics/retrieval/base.py_retrieval_aggregaters f # v{{}E1EEh"%+v}}P6==S=3I3P3PPe"{vzz|J s 0C0J0JJe"{vzz|J s 0C0J0JJ v3 ''c eZdZUdZdZeed<dZeed<dZeed<e e ed<e e ed<e e ed < dd e d e e d eedefdedd f fd Zde d e de dd fdZde fdZede d e de fdZxZS)RetrievalMetricaQ Works with binary target data. Accepts float predictions from a model output. As input to ``forward`` and ``update`` the metric accepts the following input: - ``preds`` (:class:`~torch.Tensor`): A float tensor of shape ``(N, ...)`` - ``target`` (:class:`~torch.Tensor`): A long or bool tensor of shape ``(N, ...)`` - ``indexes`` (:class:`~torch.Tensor`): A long tensor of shape ``(N, ...)`` which indicate to which query a prediction belongs .. hint:: The ``indexes``, ``preds`` and ``target`` must have the same dimension and will be flattened to single dimension once provided. .. attention:: Predictions will be first grouped by ``indexes`` and then the real metric, defined by overriding the `_metric` method, will be computed as the mean of the scores over each query. As output to ``forward`` and ``compute`` the metric returns the following output: - ``metric`` (:class:`~torch.Tensor`): A tensor as computed by ``_metric`` if the number of positive targets is at least 1, otherwise behave as specified by ``self.empty_target_action``. Args: empty_target_action: Specify what to do with queries that do not have at least a positive or negative (depend on metric) target. Choose from: - ``'neg'``: those queries count as ``0.0`` (default) - ``'pos'``: those queries count as ``1.0`` - ``'skip'``: skip those queries; if all queries are skipped, ``0.0`` is returned - ``'error'``: raise a ``ValueError`` ignore_index: Ignore predictions where the target is equal to this number. aggregation: Specify how to aggregate over indexes. Can either a custom callable function that takes in a single tensor and returns a scalar value or one of the following strings: - ``'mean'``: average value is returned - ``'median'``: median value is returned - ``'max'``: max value is returned - ``'min'``: min value is returned kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info. Raises: ValueError: If ``empty_target_action`` is not one of ``error``, ``skip``, ``neg`` or ``pos``. ValueError: If ``ignore_index`` is not `None` or an integer. Fis_differentiableThigher_is_betterfull_state_updateindexespredstargetNempty_target_action ignore_indexrrkwargsrc tt|d i|d|_d}||vrtd|d||_|t |t s td||_|dvst|std|d||_ |jd gd |jd gd |jd gd y)NF)errorskipnegposz7Argument `empty_target_action` received a wrong value `z`.z3Argument `ignore_index` must be an integer or None.rzArgument `aggregation` must be one of `mean`, `median`, `min`, `max` or a custom callable functionwhich takes tensor of values, but got .r$)defaultdist_reduce_fxr%r&) super__init__allow_non_binary_target ValueErrorr' isinstanceintr(callabler add_state)selfr'r(rr)empty_target_action_options __class__s rr4zRetrievalMetric.__init__is "6"',$&E# &A AVWjVkkmno o#6  #J|S,IRS S(??8KCX99D QH ' y"TB w4@ xDArc| tdt||||j|j\}}}|jj ||j j ||jj |y)zGCheck shape, check and convert dtypes, flatten and add to accumulators.Nz!Argument `indexes` cannot be None)r5r()r6rr5r(r$appendr%r&)r;r%r&r$s rupdatezRetrievalMetric.updatest ?@A A!8 UFD>@GGI '* KK{ 2EKK YZ4[( #J ??$++w6$%jkk++u4JJvc{+--6JJvc{+ 4<< K@A(  ' #4N#QQTT%[#4N(OQUQaQab bc{~~e$$5OsG cy)zCompute a metric over a predictions and target of a single group. This method should be overridden by subclasses. Nr2)r;r%r&s rrJzRetrievalMetric._metricsr)r-Nr)__name__ __module__ __qualname____doc__r!bool__annotations__r"r#rr strrr8r r rrr4r@rSrrJ __classcell__)r=s@rr r +s3j$t#!d!#t# &\ < L$)&*PV B BsmB7#ABHLM B  B  B< #F #F #V # ##%#%J V V   rr )rN)abcrrtypingrrrrr rBr r typing_extensionsr torchmetricsr torchmetrics.utilities.checksrtorchmetrics.utilities.datarrr8rr r2rrrcsy$77 %AH MS( (w=>HI( #( ("T fcT r