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goro

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Descripción general

Goro es una biblioteca de aprendizaje automático de alto nivel para GO construido en Gorgonia. Su objetivo es tener la misma sensación que Keras.

Uso

 import (
    . "github.com/aunum/goro/pkg/v1/model"
    "github.com/aunum/goro/pkg/v1/layer"
)

// create the 'x' input e.g. mnist image
x := NewInput ( "x" , [] int { 1 , 28 , 28 })

// create the 'y' or expect output e.g. labels
y := NewInput ( "y" , [] int { 10 })

// create a new sequential model with the name 'mnist'
model , _ := NewSequential ( "mnist" )

// add layers to the model
model . AddLayers (
    layer. Conv2D { Input : 1 , Output : 32 , Width : 3 , Height : 3 },
    layer. MaxPooling2D {},
    layer. Conv2D { Input : 32 , Output : 64 , Width : 3 , Height : 3 },
    layer. MaxPooling2D {},
    layer. Conv2D { Input : 64 , Output : 128 , Width : 3 , Height : 3 },
    layer. MaxPooling2D {},
    layer. Flatten {},
    layer. FC { Input : 128 * 3 * 3 , Output : 100 },
    layer. FC { Input : 100 , Output : 10 , Activation : layer . Softmax },
)

// pick an optimizer
optimizer := g . NewRMSPropSolver ()

// compile the model with options
model . Compile ( xi , yi ,
    WithOptimizer ( optimizer ),
    WithLoss ( m . CrossEntropy ),
    WithBatchSize ( 100 ),
)

// fit the model
model . Fit ( xTrain , yTrain )

// use the model to predict an 'x'
prediction , _ := model . Predict ( xTest )

// fit the model with a batch
model . FitBatch ( xTrainBatch , yTrainBatch )

// use the model to predict a batch of 'x'
prediction , _ = model . PredictBatch ( xTestBatch )