{- | Provides collection of functions that are used to judge the performance of models.

'MetricFn' type alias represents those functions, and "Synapse" offers a variety of them.
-}


module Synapse.NN.Metrics
    ( -- 'MetricFn' type alias and 'Metric' newtype

      MetricFn
    , lossFnToMetricFn
    
    , Metric (Metric, unMetric)
    ) where


import Synapse.NN.Losses (LossFn)

import Synapse.Tensors.Mat (Mat)

import Synapse.Autograd (Symbol(unSymbol), constSymbol)


-- | 'MetricFn' type alias represents functions that are able to provide a reference of performance of neural network model.
type MetricFn a = Mat a -> Mat a -> Mat a

-- | Converts any loss function to a metric function (because the same constraint is imposed on both 'MetricFn' and 'LossFn').
lossFnToMetricFn :: LossFn a -> MetricFn a
lossFnToMetricFn loss true predicted = unSymbol $ loss (constSymbol true) (constSymbol predicted)


{- | 'Metric' newtype wraps 'MetricFn's - functions that are able to provide a reference of performance of neural network model.

Every metric function must return symbol of singleton matrix.
-}
newtype Metric a = Metric 
    { unMetric :: MetricFn a  -- ^ Unwraps 'Metric' newtype.
    }